--- _id: '10045' abstract: - lang: eng text: "Given a fixed finite metric space (V,μ), the {\\em minimum 0-extension problem}, denoted as 0-Ext[μ], is equivalent to the following optimization problem: minimize function of the form minx∈Vn∑ifi(xi)+∑ijcijμ(xi,xj) where cij,cvi are given nonnegative costs and fi:V→R are functions given by fi(xi)=∑v∈Vcviμ(xi,v). The computational complexity of 0-Ext[μ] has been recently established by Karzanov and by Hirai: if metric μ is {\\em orientable modular} then 0-Ext[μ] can be solved in polynomial time, otherwise 0-Ext[μ] is NP-hard. To prove the tractability part, Hirai developed a theory of discrete convex functions on orientable modular graphs generalizing several known classes of functions in discrete convex analysis, such as L♮-convex functions. We consider a more general version of the problem in which unary functions fi(xi) can additionally have terms of the form cuv;iμ(xi,{u,v}) for {u,v}∈F, where set F⊆(V2) is fixed. We extend the complexity classification above by providing an explicit condition on (μ,F) for the problem to be tractable. In order to prove the tractability part, we generalize Hirai's theory and define a larger class of discrete convex functions. It covers, in particular, another well-known class of functions, namely submodular functions on an integer lattice. Finally, we improve the complexity of Hirai's algorithm for solving 0-Ext on orientable modular graphs.\r\n" article_number: '2109.10203' article_processing_charge: No arxiv: 1 author: - first_name: Martin full_name: Dvorak, Martin id: 40ED02A8-C8B4-11E9-A9C0-453BE6697425 last_name: Dvorak orcid: 0000-0001-5293-214X - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Dvorak M, Kolmogorov V. Generalized minimum 0-extension problem and discrete convexity. arXiv. doi:10.48550/arXiv.2109.10203 apa: Dvorak, M., & Kolmogorov, V. (n.d.). Generalized minimum 0-extension problem and discrete convexity. arXiv. https://doi.org/10.48550/arXiv.2109.10203 chicago: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2109.10203. ieee: M. Dvorak and V. Kolmogorov, “Generalized minimum 0-extension problem and discrete convexity,” arXiv. . ista: Dvorak M, Kolmogorov V. Generalized minimum 0-extension problem and discrete convexity. arXiv, 2109.10203. mla: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” ArXiv, 2109.10203, doi:10.48550/arXiv.2109.10203. short: M. Dvorak, V. Kolmogorov, ArXiv (n.d.). date_created: 2021-09-27T10:48:23Z date_published: 2021-09-21T00:00:00Z date_updated: 2023-05-03T10:40:16Z day: '21' ddc: - '004' department: - _id: GradSch - _id: VlKo doi: 10.48550/arXiv.2109.10203 external_id: arxiv: - '2109.10203' file: - access_level: open_access checksum: e7e83065f7bc18b9c188bf93b5ca5db6 content_type: application/pdf creator: mdvorak date_created: 2021-09-27T10:54:51Z date_updated: 2021-09-27T10:54:51Z file_id: '10046' file_name: Generalized-0-Ext.pdf file_size: 603672 relation: main_file success: 1 file_date_updated: 2021-09-27T10:54:51Z has_accepted_license: '1' keyword: - minimum 0-extension problem - metric labeling problem - discrete metric spaces - metric extensions - computational complexity - valued constraint satisfaction problems - discrete convex analysis - L-convex functions language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.48550/arXiv.2109.10203' month: '09' oa: 1 oa_version: Preprint publication: arXiv publication_status: submitted status: public title: Generalized minimum 0-extension problem and discrete convexity type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '10058' abstract: - lang: eng text: 'Quantum information and computation has become a vast field paved with opportunities for researchers and investors. As large multinational companies and international funds are heavily investing in quantum technologies it is still a question which platform is best suited for the task of realizing a scalable quantum processor. In this work we investigate hole spins in Ge quantum wells. These hold great promise as they possess several favorable properties: a small effective mass, a strong spin-orbit coupling, long relaxation time and an inherent immunity to hyperfine noise. All these characteristics helped Ge hole spin qubits to evolve from a single qubit to a fully entangled four qubit processor in only 3 years. Here, we investigated a qubit approach leveraging the large out-of-plane g-factors of heavy hole states in Ge quantum dots. We found this qubit to be reproducibly operable at extremely low magnetic field and at large speeds while maintaining coherence. This was possible because large differences of g-factors in adjacent dots can be achieved in the out-of-plane direction. In the in-plane direction the small g-factors, on the other hand, can be altered very effectively by the confinement potentials. Here, we found that this can even lead to a sign change of the g-factors. The resulting g-factor difference alters the dynamics of the system drastically and produces effects typically attributed to a spin-orbit induced spin-flip term. The investigations carried out in this thesis give further insights into the possibilities of holes in Ge and reveal new physical properties that need to be considered when designing future spin qubit experiments.' acknowledged_ssus: - _id: M-Shop - _id: NanoFab acknowledgement: The author gratefully acknowledges support by the Austrian Science Fund (FWF), grants No P30207, and the Nomis foundation. alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Daniel full_name: Jirovec, Daniel id: 4C473F58-F248-11E8-B48F-1D18A9856A87 last_name: Jirovec orcid: 0000-0002-7197-4801 citation: ama: Jirovec D. Singlet-Triplet qubits and spin-orbit interaction in 2-dimensional Ge hole gases. 2021. doi:10.15479/at:ista:10058 apa: Jirovec, D. (2021). Singlet-Triplet qubits and spin-orbit interaction in 2-dimensional Ge hole gases. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10058 chicago: Jirovec, Daniel. “Singlet-Triplet Qubits and Spin-Orbit Interaction in 2-Dimensional Ge Hole Gases.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10058. ieee: D. Jirovec, “Singlet-Triplet qubits and spin-orbit interaction in 2-dimensional Ge hole gases,” Institute of Science and Technology Austria, 2021. ista: Jirovec D. 2021. Singlet-Triplet qubits and spin-orbit interaction in 2-dimensional Ge hole gases. Institute of Science and Technology Austria. mla: Jirovec, Daniel. Singlet-Triplet Qubits and Spin-Orbit Interaction in 2-Dimensional Ge Hole Gases. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10058. short: D. Jirovec, Singlet-Triplet Qubits and Spin-Orbit Interaction in 2-Dimensional Ge Hole Gases, Institute of Science and Technology Austria, 2021. date_created: 2021-09-30T07:53:49Z date_published: 2021-10-05T00:00:00Z date_updated: 2023-09-08T11:41:08Z day: '05' ddc: - '621' - '539' degree_awarded: PhD department: - _id: GradSch - _id: GeKa doi: 10.15479/at:ista:10058 file: - access_level: closed checksum: ad6bcb24083ed7c02baaf1885c9ea3d5 content_type: application/x-zip-compressed creator: djirovec date_created: 2021-09-30T14:29:14Z date_updated: 2022-12-20T23:30:07Z embargo_to: open_access file_id: '10061' file_name: PHD_Thesis_Jirovec_Source.zip file_size: 32397600 relation: source_file - access_level: open_access checksum: 5fbe08d4f66d1153e04c47971538fae8 content_type: application/pdf creator: djirovec date_created: 2021-10-05T07:56:49Z date_updated: 2022-12-20T23:30:07Z embargo: 2022-10-06 file_id: '10087' file_name: PHD_Thesis_pdfa2b_1.pdf file_size: 26910829 relation: main_file file_date_updated: 2022-12-20T23:30:07Z has_accepted_license: '1' keyword: - qubits - quantum computing - holes language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '10' oa: 1 oa_version: Published Version page: '151' project: - _id: 2641CE5E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P30207 name: Hole spin orbit qubits in Ge quantum wells publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '8831' relation: part_of_dissertation status: public - id: '10065' relation: part_of_dissertation status: public - id: '10066' relation: part_of_dissertation status: public - id: '8909' relation: part_of_dissertation status: public - id: '5816' relation: part_of_dissertation status: public status: public supervisor: - first_name: Georgios full_name: Katsaros, Georgios id: 38DB5788-F248-11E8-B48F-1D18A9856A87 last_name: Katsaros orcid: 0000-0001-8342-202X title: Singlet-Triplet qubits and spin-orbit interaction in 2-dimensional Ge hole gases tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10077' abstract: - lang: eng text: Although much is known about how single neurons in the hippocampus represent an animal’s position, how cell-cell interactions contribute to spatial coding remains poorly understood. Using a novel statistical estimator and theoretical modeling, both developed in the framework of maximum entropy models, we reveal highly structured cell-to-cell interactions whose statistics depend on familiar vs. novel environment. In both conditions the circuit interactions optimize the encoding of spatial information, but for regimes that differ in the signal-to-noise ratio of their spatial inputs. Moreover, the topology of the interactions facilitates linear decodability, making the information easy to read out by downstream circuits. These findings suggest that the efficient coding hypothesis is not applicable only to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain. acknowledgement: We thank Peter Baracskay, Karola Kaefer and Hugo Malagon-Vina for the acquisition of the data. We thank Federico Stella for comments on an earlier version of the manuscript. MN was supported by European Union Horizon 2020 grant 665385, JC was supported by European Research Council consolidator grant 281511, GT was supported by the Austrian Science Fund (FWF) grant P34015, CS was supported by an IST fellow grant, National Institute of Mental Health Award 1R01MH125571-01, by the National Science Foundation under NSF Award No. 1922658 and a Google faculty award. article_processing_charge: No author: - first_name: Michele full_name: Nardin, Michele id: 30BD0376-F248-11E8-B48F-1D18A9856A87 last_name: Nardin orcid: 0000-0001-8849-6570 - first_name: Jozsef L full_name: Csicsvari, Jozsef L id: 3FA14672-F248-11E8-B48F-1D18A9856A87 last_name: Csicsvari orcid: 0000-0002-5193-4036 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin citation: ama: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv. doi:10.1101/2021.09.28.460602 apa: Nardin, M., Csicsvari, J. L., Tkačik, G., & Savin, C. (n.d.). The structure of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2021.09.28.460602 chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin. “The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2021.09.28.460602. ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal CA1 interactions optimizes spatial coding across experience,” bioRxiv. Cold Spring Harbor Laboratory. ista: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv, 10.1101/2021.09.28.460602. mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience.” BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/2021.09.28.460602. short: M. Nardin, J.L. Csicsvari, G. Tkačik, C. Savin, BioRxiv (n.d.). date_created: 2021-10-04T06:23:34Z date_published: 2021-09-29T00:00:00Z date_updated: 2024-03-25T23:30:09Z day: '29' department: - _id: GradSch - _id: JoCs - _id: GaTk doi: 10.1101/2021.09.28.460602 ec_funded: 1 language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/2021.09.28.460602 month: '09' oa: 1 oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 257A4776-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '281511' name: Memory-related information processing in neuronal circuits of the hippocampus and entorhinal cortex - _id: 626c45b5-2b32-11ec-9570-e509828c1ba6 grant_number: P34015 name: Efficient coding with biophysical realism publication: bioRxiv publication_status: submitted publisher: Cold Spring Harbor Laboratory related_material: record: - id: '11932' relation: dissertation_contains status: public status: public title: The structure of hippocampal CA1 interactions optimizes spatial coding across experience tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '10080' abstract: - lang: eng text: Hippocampal and neocortical neural activity is modulated by the position of the individual in space. While hippocampal neurons provide the basis for a spatial map, prefrontal cortical neurons generalize over environmental features. Whether these generalized representations result from a bidirectional interaction with, or are mainly derived from hippocampal spatial representations is not known. By examining simultaneously recorded hippocampal and medial prefrontal neurons, we observed that prefrontal spatial representations show a delayed coherence with hippocampal ones. We also identified subpopulations of cells in the hippocampus and medial prefrontal cortex that formed functional cross-area couplings; these resembled the optimal connections predicted by a probabilistic model of spatial information transfer and generalization. Moreover, cross-area couplings were strongest and had the shortest delay preceding spatial decision-making. Our results suggest that generalized spatial coding in the medial prefrontal cortex is inherited from spatial representations in the hippocampus, and that the routing of information can change dynamically with behavioral demands. acknowledgement: We thank Federico Stella for invaluable suggestions and discussions. We thank Yosman BapatDhar and Andrea Cumpelik for comments, help and suggestions on the exposure of the text. We thank Predrag Živadinović and Juliana Couras for comments on the text and the figures. This work was supported by the EU-FP7 MC-ITN IN-SENS (grant 607616). article_processing_charge: No author: - first_name: Michele full_name: Nardin, Michele id: 30BD0376-F248-11E8-B48F-1D18A9856A87 last_name: Nardin orcid: 0000-0001-8849-6570 - first_name: Karola full_name: Käfer, Karola id: 2DAA49AA-F248-11E8-B48F-1D18A9856A87 last_name: Käfer - first_name: Jozsef L full_name: Csicsvari, Jozsef L id: 3FA14672-F248-11E8-B48F-1D18A9856A87 last_name: Csicsvari orcid: 0000-0002-5193-4036 citation: ama: Nardin M, Käfer K, Csicsvari JL. The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus. bioRxiv. doi:10.1101/2021.09.30.462269 apa: Nardin, M., Käfer, K., & Csicsvari, J. L. (n.d.). The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2021.09.30.462269 chicago: Nardin, Michele, Karola Käfer, and Jozsef L Csicsvari. “The Generalized Spatial Representation in the Prefrontal Cortex Is Inherited from the Hippocampus.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2021.09.30.462269. ieee: M. Nardin, K. Käfer, and J. L. Csicsvari, “The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus,” bioRxiv. Cold Spring Harbor Laboratory. ista: Nardin M, Käfer K, Csicsvari JL. The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus. bioRxiv, 10.1101/2021.09.30.462269. mla: Nardin, Michele, et al. “The Generalized Spatial Representation in the Prefrontal Cortex Is Inherited from the Hippocampus.” BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/2021.09.30.462269. short: M. Nardin, K. Käfer, J.L. Csicsvari, BioRxiv (n.d.). date_created: 2021-10-04T06:28:32Z date_published: 2021-10-02T00:00:00Z date_updated: 2021-10-05T12:34:26Z day: '02' department: - _id: GradSch - _id: JoCs doi: 10.1101/2021.09.30.462269 ec_funded: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://www.biorxiv.org/content/10.1101/2021.09.30.462269 month: '10' oa: 1 oa_version: Preprint project: - _id: 257BBB4C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '607616' name: Inter-and intracellular signalling in schizophrenia publication: bioRxiv publication_status: submitted publisher: Cold Spring Harbor Laboratory status: public title: The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '10083' abstract: - lang: eng text: "Plant motions occur across a wide spectrum of timescales, ranging from seed dispersal through bursting (milliseconds) and stomatal opening (minutes) to long-term adaptation of gross architecture. Relatively fast motions include water-driven growth as exemplified by root cell expansion under abiotic/biotic stresses or during gravitropism. A showcase is a root growth inhibition in 30 seconds triggered by the phytohormone auxin. However, the cellular and molecular mechanisms are still largely unknown. This thesis covers the studies about this topic as follows. By taking advantage of microfluidics combined with live imaging, pharmaceutical tools, and transgenic lines, we examined the kinetics of and causal relationship among various auxininduced rapid cellular changes in root growth, apoplastic pH, cytosolic Ca2+, cortical microtubule (CMT) orientation, and vacuolar morphology. We revealed that CMT reorientation and vacuolar constriction are the consequence of growth itself instead of responding directly to auxin. In contrast, auxin induces apoplast alkalinization to rapidly inhibit root growth in 30 seconds. This auxin-triggered apoplast alkalinization results from rapid H+- influx that is contributed by Ca2+ inward channel CYCLIC NUCLEOTIDE-GATED CHANNEL 14 (CNGC14)-dependent Ca2+ signaling. To dissect which auxin signaling mediates the rapid apoplast alkalinization, we\r\ncombined microfluidics and genetic engineering to verify that TIR1/AFB receptors conduct a non-transcriptional regulation on Ca2+ and H+ -influx. This non-canonical pathway is mostly mediated by the cytosolic portion of TIR1/AFB. On the other hand, we uncovered, using biochemical and phospho-proteomic analysis, that auxin cell surface signaling component TRANSMEMBRANE KINASE 1 (TMK1) plays a negative role during auxin-trigger apoplast\r\nalkalinization and root growth inhibition through directly activating PM H+ -ATPases. Therefore, we discovered that PM H+ -ATPases counteract instead of mediate the auxintriggered rapid H+ -influx, and that TIR1/AFB and TMK1 regulate root growth antagonistically. This opposite effect of TIR1/AFB and TMK1 is consistent during auxin-induced hypocotyl elongation, leading us to explore the relation of two signaling pathways. Assisted with biochemistry and fluorescent imaging, we verified for the first time that TIR1/AFB and TMK1 can interact with each other. The ability of TIR1/AFB binding to membrane lipid provides a basis for the interaction of plasma membrane- and cytosol-localized proteins.\r\nBesides, transgenic analysis combined with genetic engineering and biochemistry showed that vi\r\nthey do function in the same pathway. Particularly, auxin-induced TMK1 increase is TIR1/AFB dependent, suggesting TIR1/AFB regulation on TMK1. Conversely, TMK1 also regulates TIR1/AFB protein levels and thus auxin canonical signaling. To follow the study of rapid growth regulation, we analyzed another rapid growth regulator, signaling peptide RALF1. We showed that RALF1 also triggers a rapid and reversible growth inhibition caused by H + influx, highly resembling but not dependent on auxin. Besides, RALF1 promotes auxin biosynthesis by increasing expression of auxin biosynthesis enzyme YUCCAs and thus induces auxin signaling in ca. 1 hour, contributing to the sustained RALF1-triggered growth inhibition. These studies collectively contribute to understanding rapid regulation on plant cell\r\ngrowth, novel auxin signaling pathway as well as auxin-peptide crosstalk. " alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Lanxin full_name: Li, Lanxin last_name: Li citation: ama: Li L. Rapid cell growth regulation in Arabidopsis. 2021. doi:10.15479/at:ista:10083 apa: Li, L. (2021). Rapid cell growth regulation in Arabidopsis. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10083 chicago: Li, Lanxin. “Rapid Cell Growth Regulation in Arabidopsis.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10083. ieee: L. Li, “Rapid cell growth regulation in Arabidopsis,” Institute of Science and Technology Austria, 2021. ista: Li L. 2021. Rapid cell growth regulation in Arabidopsis. Institute of Science and Technology Austria. mla: Li, Lanxin. Rapid Cell Growth Regulation in Arabidopsis. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10083. short: L. Li, Rapid Cell Growth Regulation in Arabidopsis, Institute of Science and Technology Austria, 2021. date_created: 2021-10-04T13:33:10Z date_published: 2021-10-06T00:00:00Z date_updated: 2025-05-07T11:12:33Z day: '06' ddc: - '575' degree_awarded: PhD department: - _id: GradSch - _id: JiFr doi: 10.15479/at:ista:10083 ec_funded: 1 file: - access_level: open_access checksum: 3b2f55b3b8ae05337a0dcc1cd8595b10 content_type: application/pdf creator: cchlebak date_created: 2021-10-14T08:00:07Z date_updated: 2022-12-20T23:30:03Z embargo: 2022-10-14 file_id: '10138' file_name: 0._IST_Austria_Thesis_Lanxin_Li_1014_pdftron.pdf file_size: 8616142 relation: main_file - access_level: closed checksum: f23ed258ca894f6aabf58b0c128bf242 content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: cchlebak date_created: 2021-10-14T08:00:13Z date_updated: 2022-12-20T23:30:03Z embargo_to: open_access file_id: '10139' file_name: 0._IST_Austria_Thesis_Lanxin_Li_1014.docx file_size: 15058499 relation: source_file file_date_updated: 2022-12-20T23:30:03Z has_accepted_license: '1' language: - iso: eng month: '10' oa: 1 oa_version: Published Version project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 26B4D67E-B435-11E9-9278-68D0E5697425 grant_number: '25351' name: 'A Case Study of Plant Growth Regulation: Molecular Mechanism of Auxin-mediated Rapid Growth Inhibition in Arabidopsis Root' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '442' relation: part_of_dissertation status: public - id: '8931' relation: part_of_dissertation status: public - id: '9287' relation: part_of_dissertation status: public - id: '8283' relation: part_of_dissertation status: public - id: '8986' relation: part_of_dissertation status: public - id: '10015' relation: part_of_dissertation status: public - id: '10095' relation: part_of_dissertation status: public - id: '6627' relation: part_of_dissertation status: public status: public supervisor: - first_name: Jiří full_name: Friml, Jiří id: 4159519E-F248-11E8-B48F-1D18A9856A87 last_name: Friml orcid: 0000-0002-8302-7596 title: Rapid cell growth regulation in Arabidopsis tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10135' abstract: - lang: eng text: "Plants maintain the capacity to develop new organs e.g. lateral roots post-embryonically throughout their whole life and thereby flexibly adapt to ever-changing environmental conditions. Plant hormones auxin and cytokinin are the main regulators of the lateral root organogenesis. Additionally to their solo activities, the interaction between auxin and\r\ncytokinin plays crucial role in fine-tuning of lateral root development and growth. In particular, cytokinin modulates auxin distribution within the developing lateral root by affecting the endomembrane trafficking of auxin transporter PIN1 and promoting its vacuolar degradation (Marhavý et al., 2011, 2014). This effect is independent of transcription and\r\ntranslation. Therefore, it suggests novel, non-canonical cytokinin activity occuring possibly on the posttranslational level. Impact of cytokinin and other plant hormones on auxin transporters (including PIN1) on the posttranslational level is described in detail in the introduction part of this thesis in a form of a review (Semeradova et al., 2020). To gain insights into the molecular machinery underlying cytokinin effect on the endomembrane trafficking in the plant cell, in particular on the PIN1 degradation, we conducted two large proteomic screens: 1) Identification of cytokinin binding proteins using\r\nchemical proteomics. 2) Monitoring of proteomic and phosphoproteomic changes upon cytokinin treatment. In the first screen, we identified DYNAMIN RELATED PROTEIN 2A (DRP2A). We found that DRP2A plays a role in cytokinin regulated processes during the plant growth and that cytokinin treatment promotes destabilization of DRP2A protein. However, the role of DRP2A in the PIN1 degradation remains to be elucidated. In the second screen, we found VACUOLAR PROTEIN SORTING 9A (VPS9A). VPS9a plays crucial role in plant’s response to cytokin and in cytokinin mediated PIN1 degradation. Altogether, we identified proteins, which bind to cytokinin and proteins that in response to\r\ncytokinin exhibit significantly changed abundance or phosphorylation pattern. By combining information from these two screens, we can pave our way towards understanding of noncanonical cytokinin effects." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Hana full_name: Semerádová, Hana id: 42FE702E-F248-11E8-B48F-1D18A9856A87 last_name: Semerádová citation: ama: Semerádová H. Molecular mechanisms of the cytokinin-regulated endomembrane trafficking to coordinate plant organogenesis. 2021. doi:10.15479/at:ista:10135 apa: Semerádová, H. (2021). Molecular mechanisms of the cytokinin-regulated endomembrane trafficking to coordinate plant organogenesis. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10135 chicago: Semerádová, Hana. “Molecular Mechanisms of the Cytokinin-Regulated Endomembrane Trafficking to Coordinate Plant Organogenesis.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10135. ieee: H. Semerádová, “Molecular mechanisms of the cytokinin-regulated endomembrane trafficking to coordinate plant organogenesis,” Institute of Science and Technology Austria, 2021. ista: Semerádová H. 2021. Molecular mechanisms of the cytokinin-regulated endomembrane trafficking to coordinate plant organogenesis. Institute of Science and Technology Austria. mla: Semerádová, Hana. Molecular Mechanisms of the Cytokinin-Regulated Endomembrane Trafficking to Coordinate Plant Organogenesis. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10135. short: H. Semerádová, Molecular Mechanisms of the Cytokinin-Regulated Endomembrane Trafficking to Coordinate Plant Organogenesis, Institute of Science and Technology Austria, 2021. date_created: 2021-10-13T13:42:48Z date_published: 2021-10-13T00:00:00Z date_updated: 2024-01-25T10:53:29Z day: '13' ddc: - '570' degree_awarded: PhD department: - _id: GradSch - _id: EvBe doi: 10.15479/at:ista:10135 file: - access_level: closed checksum: ce7108853e6cec6224f17cd6429b51fe content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: cziletti date_created: 2021-10-27T07:45:37Z date_updated: 2022-12-20T23:30:05Z embargo_to: open_access file_id: '10186' file_name: Hana_Semeradova_Disertation_Thesis_II_Revised_3.docx file_size: 28508629 relation: source_file - access_level: open_access checksum: 0d7afb846e8e31ec794de47bf44e12ef content_type: application/pdf creator: cziletti date_created: 2021-10-27T07:45:57Z date_updated: 2022-12-20T23:30:05Z embargo: 2022-10-28 file_id: '10187' file_name: Hana_Semeradova_Disertation_Thesis_II_Revised_3PDFA.pdf file_size: 10623525 relation: main_file file_date_updated: 2022-12-20T23:30:05Z has_accepted_license: '1' language: - iso: eng month: '10' oa: 1 oa_version: Published Version project: - _id: 261821BC-B435-11E9-9278-68D0E5697425 grant_number: '24746' name: Molecular mechanisms of the cytokinin regulated endomembrane trafficking to coordinate plant organogenesis. publication_identifier: isbn: - 978-3-99078-014-5 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '9160' relation: part_of_dissertation status: public status: public supervisor: - first_name: Eva full_name: Benková, Eva id: 38F4F166-F248-11E8-B48F-1D18A9856A87 last_name: Benková orcid: 0000-0002-8510-9739 title: Molecular mechanisms of the cytokinin-regulated endomembrane trafficking to coordinate plant organogenesis type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '10191' abstract: - lang: eng text: "In this work we solve the algorithmic problem of consistency verification for the TSO and PSO memory models given a reads-from map, denoted VTSO-rf and VPSO-rf, respectively. For an execution of n events over k threads and d variables, we establish novel bounds that scale as nk+1 for TSO and as nk+1· min(nk2, 2k· d) for PSO. Moreover, based on our solution to these problems, we develop an SMC algorithm under TSO and PSO that uses the RF equivalence. The algorithm is exploration-optimal, in the sense that it is guaranteed to explore each class of the RF partitioning exactly once, and spends polynomial time per class when k is bounded. Finally, we implement all our algorithms in the SMC tool Nidhugg, and perform a large number of experiments over benchmarks from existing literature. Our experimental results show that our algorithms for VTSO-rf and VPSO-rf provide significant scalability improvements over standard alternatives. Moreover, when used for SMC, the RF partitioning is often much coarser than the standard Shasha-Snir partitioning for TSO/PSO, which yields a significant speedup in the model checking task.\r\n\r\n" acknowledgement: "The research was partially funded by the ERC CoG 863818 (ForM-SMArt) and the Vienna Science\r\nand Technology Fund (WWTF) through project ICT15-003." article_number: '164' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Truc Lam full_name: Bui, Truc Lam last_name: Bui - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Tushar full_name: Gautam, Tushar last_name: Gautam - first_name: Andreas full_name: Pavlogiannis, Andreas id: 49704004-F248-11E8-B48F-1D18A9856A87 last_name: Pavlogiannis orcid: 0000-0002-8943-0722 - first_name: Viktor full_name: Toman, Viktor id: 3AF3DA7C-F248-11E8-B48F-1D18A9856A87 last_name: Toman orcid: 0000-0001-9036-063X citation: ama: Bui TL, Chatterjee K, Gautam T, Pavlogiannis A, Toman V. The reads-from equivalence for the TSO and PSO memory models. Proceedings of the ACM on Programming Languages. 2021;5(OOPSLA). doi:10.1145/3485541 apa: Bui, T. L., Chatterjee, K., Gautam, T., Pavlogiannis, A., & Toman, V. (2021). The reads-from equivalence for the TSO and PSO memory models. Proceedings of the ACM on Programming Languages. Association for Computing Machinery. https://doi.org/10.1145/3485541 chicago: Bui, Truc Lam, Krishnendu Chatterjee, Tushar Gautam, Andreas Pavlogiannis, and Viktor Toman. “The Reads-from Equivalence for the TSO and PSO Memory Models.” Proceedings of the ACM on Programming Languages. Association for Computing Machinery, 2021. https://doi.org/10.1145/3485541. ieee: T. L. Bui, K. Chatterjee, T. Gautam, A. Pavlogiannis, and V. Toman, “The reads-from equivalence for the TSO and PSO memory models,” Proceedings of the ACM on Programming Languages, vol. 5, no. OOPSLA. Association for Computing Machinery, 2021. ista: Bui TL, Chatterjee K, Gautam T, Pavlogiannis A, Toman V. 2021. The reads-from equivalence for the TSO and PSO memory models. Proceedings of the ACM on Programming Languages. 5(OOPSLA), 164. mla: Bui, Truc Lam, et al. “The Reads-from Equivalence for the TSO and PSO Memory Models.” Proceedings of the ACM on Programming Languages, vol. 5, no. OOPSLA, 164, Association for Computing Machinery, 2021, doi:10.1145/3485541. short: T.L. Bui, K. Chatterjee, T. Gautam, A. Pavlogiannis, V. Toman, Proceedings of the ACM on Programming Languages 5 (2021). date_created: 2021-10-27T15:05:34Z date_published: 2021-10-15T00:00:00Z date_updated: 2025-07-14T09:10:16Z day: '15' ddc: - '000' department: - _id: GradSch - _id: KrCh doi: 10.1145/3485541 ec_funded: 1 external_id: arxiv: - '2011.11763' file: - access_level: open_access checksum: 9d6dce7b611853c529bb7b1915ac579e content_type: application/pdf creator: cchlebak date_created: 2021-11-04T07:24:48Z date_updated: 2021-11-04T07:24:48Z file_id: '10215' file_name: 2021_ProcACMPL_Bui.pdf file_size: 2903485 relation: main_file success: 1 file_date_updated: 2021-11-04T07:24:48Z has_accepted_license: '1' intvolume: ' 5' issue: OOPSLA keyword: - safety - risk - reliability and quality - software language: - iso: eng month: '10' oa: 1 oa_version: Published Version project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 25892FC0-B435-11E9-9278-68D0E5697425 grant_number: ICT15-003 name: Efficient Algorithms for Computer Aided Verification publication: Proceedings of the ACM on Programming Languages publication_identifier: eissn: - 2475-1421 publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' related_material: record: - id: '10199' relation: dissertation_contains status: public scopus_import: '1' status: public title: The reads-from equivalence for the TSO and PSO memory models tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 5 year: '2021' ... --- _id: '10199' abstract: - lang: eng text: The design and verification of concurrent systems remains an open challenge due to the non-determinism that arises from the inter-process communication. In particular, concurrent programs are notoriously difficult both to be written correctly and to be analyzed formally, as complex thread interaction has to be accounted for. The difficulties are further exacerbated when concurrent programs get executed on modern-day hardware, which contains various buffering and caching mechanisms for efficiency reasons. This causes further subtle non-determinism, which can often produce very unintuitive behavior of the concurrent programs. Model checking is at the forefront of tackling the verification problem, where the task is to decide, given as input a concurrent system and a desired property, whether the system satisfies the property. The inherent state-space explosion problem in model checking of concurrent systems causes naïve explicit methods not to scale, thus more inventive methods are required. One such method is stateless model checking (SMC), which explores in memory-efficient manner the program executions rather than the states of the program. State-of-the-art SMC is typically coupled with partial order reduction (POR) techniques, which argue that certain executions provably produce identical system behavior, thus limiting the amount of executions one needs to explore in order to cover all possible behaviors. Another method to tackle the state-space explosion is symbolic model checking, where the considered techniques operate on a succinct implicit representation of the input system rather than explicitly accessing the system. In this thesis we present new techniques for verification of concurrent systems. We present several novel POR methods for SMC of concurrent programs under various models of semantics, some of which account for write-buffering mechanisms. Additionally, we present novel algorithms for symbolic model checking of finite-state concurrent systems, where the desired property of the systems is to ensure a formally defined notion of fairness. acknowledged_ssus: - _id: SSU alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Viktor full_name: Toman, Viktor id: 3AF3DA7C-F248-11E8-B48F-1D18A9856A87 last_name: Toman orcid: 0000-0001-9036-063X citation: ama: Toman V. Improved verification techniques for concurrent systems. 2021. doi:10.15479/at:ista:10199 apa: Toman, V. (2021). Improved verification techniques for concurrent systems. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10199 chicago: Toman, Viktor. “Improved Verification Techniques for Concurrent Systems.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10199. ieee: V. Toman, “Improved verification techniques for concurrent systems,” Institute of Science and Technology Austria, 2021. ista: Toman V. 2021. Improved verification techniques for concurrent systems. Institute of Science and Technology Austria. mla: Toman, Viktor. Improved Verification Techniques for Concurrent Systems. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10199. short: V. Toman, Improved Verification Techniques for Concurrent Systems, Institute of Science and Technology Austria, 2021. date_created: 2021-10-29T20:09:01Z date_published: 2021-10-31T00:00:00Z date_updated: 2025-07-14T09:10:16Z day: '31' ddc: - '000' degree_awarded: PhD department: - _id: GradSch - _id: KrCh doi: 10.15479/at:ista:10199 ec_funded: 1 file: - access_level: open_access checksum: 4f412a1ee60952221b499a4b1268df35 content_type: application/pdf creator: vtoman date_created: 2021-11-08T14:12:22Z date_updated: 2021-11-08T14:12:22Z file_id: '10225' file_name: toman_th_final.pdf file_size: 2915234 relation: main_file - access_level: closed checksum: 9584943f99127be2dd2963f6784c37d4 content_type: application/zip creator: vtoman date_created: 2021-11-08T14:12:46Z date_updated: 2021-11-09T09:00:50Z file_id: '10226' file_name: toman_thesis.zip file_size: 8616056 relation: source_file file_date_updated: 2021-11-09T09:00:50Z has_accepted_license: '1' keyword: - concurrency - verification - model checking language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: '166' project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 25F2ACDE-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11402-N23 name: Rigorous Systems Engineering - _id: 25892FC0-B435-11E9-9278-68D0E5697425 grant_number: ICT15-003 name: Efficient Algorithms for Computer Aided Verification - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '10190' relation: part_of_dissertation status: public - id: '9987' relation: part_of_dissertation status: public - id: '141' relation: part_of_dissertation status: public - id: '10191' relation: part_of_dissertation status: public status: public supervisor: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X title: Improved verification techniques for concurrent systems type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10293' abstract: - lang: eng text: "Indirect reciprocity in evolutionary game theory is a prominent mechanism for explaining the evolution of cooperation among unrelated individuals. In contrast to direct reciprocity, which is based on individuals meeting repeatedly, and conditionally cooperating by using their own experiences, indirect reciprocity is based on individuals’ reputations. If a player helps another, this increases the helper’s public standing, benefitting them in the future. This lets cooperation in the population emerge without individuals having to meet more than once. While the two modes of reciprocity are intertwined, they are difficult to compare. Thus, they are usually studied in isolation. Direct reciprocity can maintain cooperation with simple strategies, and is robust against noise even when players do not remember more\r\nthan their partner’s last action. Meanwhile, indirect reciprocity requires its successful strategies, or social norms, to be more complex. Exhaustive search previously identified eight such norms, called the “leading eight”, which excel at maintaining cooperation. However, as the first result of this thesis, we show that the leading eight break down once we remove the fundamental assumption that information is synchronized and public, such that everyone agrees on reputations. Once we consider a more realistic scenario of imperfect information, where reputations are private, and individuals occasionally misinterpret or miss observations, the leading eight do not promote cooperation anymore. Instead, minor initial disagreements can proliferate, fragmenting populations into subgroups. In a next step, we consider ways to mitigate this issue. We first explore whether introducing “generosity” can stabilize cooperation when players use the leading eight strategies in noisy environments. This approach of modifying strategies to include probabilistic elements for coping with errors is known to work well in direct reciprocity. However, as we show here, it fails for the more complex norms of indirect reciprocity. Imperfect information still prevents cooperation from evolving. On the other hand, we succeeded to show in this thesis that modifying the leading eight to use “quantitative assessment”, i.e. tracking reputation scores on a scale beyond good and bad, and making overall judgments of others based on a threshold, is highly successful, even when noise increases in the environment. Cooperation can flourish when reputations\r\nare more nuanced, and players have a broader understanding what it means to be “good.” Finally, we present a single theoretical framework that unites the two modes of reciprocity despite their differences. Within this framework, we identify a novel simple and successful strategy for indirect reciprocity, which can cope with noisy environments and has an analogue in direct reciprocity. We can also analyze decision making when different sources of information are available. Our results help highlight that for sustaining cooperation, already the most simple rules of reciprocity can be sufficient." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Laura full_name: Schmid, Laura id: 38B437DE-F248-11E8-B48F-1D18A9856A87 last_name: Schmid orcid: 0000-0002-6978-7329 citation: ama: Schmid L. Evolution of cooperation via (in)direct reciprocity under imperfect information. 2021. doi:10.15479/at:ista:10293 apa: Schmid, L. (2021). Evolution of cooperation via (in)direct reciprocity under imperfect information. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10293 chicago: Schmid, Laura. “Evolution of Cooperation via (in)Direct Reciprocity under Imperfect Information.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10293. ieee: L. Schmid, “Evolution of cooperation via (in)direct reciprocity under imperfect information,” Institute of Science and Technology Austria, 2021. ista: Schmid L. 2021. Evolution of cooperation via (in)direct reciprocity under imperfect information. Institute of Science and Technology Austria. mla: Schmid, Laura. Evolution of Cooperation via (in)Direct Reciprocity under Imperfect Information. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10293. short: L. Schmid, Evolution of Cooperation via (in)Direct Reciprocity under Imperfect Information, Institute of Science and Technology Austria, 2021. date_created: 2021-11-15T17:12:57Z date_published: 2021-11-17T00:00:00Z date_updated: 2025-07-14T09:10:09Z day: '17' ddc: - '519' - '576' degree_awarded: PhD department: - _id: GradSch - _id: KrCh doi: 10.15479/at:ista:10293 ec_funded: 1 file: - access_level: closed checksum: 86a05b430756ca12ae8107b6e6f3c1e5 content_type: application/zip creator: lschmid date_created: 2021-11-18T12:41:46Z date_updated: 2022-12-20T23:30:08Z embargo_to: open_access file_id: '10305' file_name: submission_new.zip file_size: 29703124 relation: source_file - access_level: open_access checksum: d940af042e94660c6b6a7b4f0b184d47 content_type: application/pdf creator: lschmid date_created: 2021-11-18T12:59:15Z date_updated: 2022-12-20T23:30:08Z embargo: 2022-10-18 file_id: '10306' file_name: thesis_new_upload.pdf file_size: 8320985 relation: main_file file_date_updated: 2022-12-20T23:30:08Z has_accepted_license: '1' language: - iso: eng month: '11' oa: 1 oa_version: Published Version page: '171' project: - _id: 2581B60A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '279307' name: 'Quantitative Graph Games: Theory and Applications' - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 2584A770-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 23499-N23 name: Modern Graph Algorithmic Techniques in Formal Verification - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '9997' relation: part_of_dissertation status: public - id: '2' relation: part_of_dissertation status: public - id: '9402' relation: part_of_dissertation status: public status: public supervisor: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X title: Evolution of cooperation via (in)direct reciprocity under imperfect information type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10303' abstract: - lang: eng text: 'Nitrogen is an essential macronutrient determining plant growth, development and affecting agricultural productivity. Root, as a hub that perceives and integrates local and systemic signals on the plant’s external and endogenous nitrogen resources, communicates with other plant organs to consolidate their physiology and development in accordance with actual nitrogen balance. Over the last years, numerous studies demonstrated that these comprehensive developmental adaptations rely on the interaction between pathways controlling nitrogen homeostasis and hormonal networks acting globally in the plant body. However, molecular insights into how the information about the nitrogen status is translated through hormonal pathways into specific developmental output are lacking. In my work, I addressed so far poorly understood mechanisms underlying root-to-shoot communication that lead to a rapid re-adjustment of shoot growth and development after nitrate provision. Applying a combination of molecular, cell, and developmental biology approaches, genetics and grafting experiments as well as hormonal analytics, I identified and characterized an unknown molecular framework orchestrating shoot development with a root nitrate sensory system. ' acknowledged_ssus: - _id: LifeSc - _id: Bio alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Rashed full_name: Abualia, Rashed id: 4827E134-F248-11E8-B48F-1D18A9856A87 last_name: Abualia orcid: 0000-0002-9357-9415 citation: ama: Abualia R. Role of hormones in nitrate regulated growth. 2021. doi:10.15479/at:ista:10303 apa: Abualia, R. (2021). Role of hormones in nitrate regulated growth. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10303 chicago: Abualia, Rashed. “Role of Hormones in Nitrate Regulated Growth.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10303. ieee: R. Abualia, “Role of hormones in nitrate regulated growth,” Institute of Science and Technology Austria, 2021. ista: Abualia R. 2021. Role of hormones in nitrate regulated growth. Institute of Science and Technology Austria. mla: Abualia, Rashed. Role of Hormones in Nitrate Regulated Growth. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10303. short: R. Abualia, Role of Hormones in Nitrate Regulated Growth, Institute of Science and Technology Austria, 2021. date_created: 2021-11-18T11:20:59Z date_published: 2021-11-22T00:00:00Z date_updated: 2023-09-19T14:42:45Z day: '22' ddc: - '580' - '581' degree_awarded: PhD department: - _id: GradSch - _id: EvBe doi: 10.15479/at:ista:10303 file: - access_level: open_access checksum: dea38b98aa4da1cea03dcd0f10862818 content_type: application/pdf creator: rabualia date_created: 2021-11-22T14:48:21Z date_updated: 2022-12-20T23:30:06Z embargo: 2022-11-23 file_id: '10331' file_name: AbualiaPhDthesisfinalv3.pdf file_size: 28005730 relation: main_file - access_level: closed checksum: 4cd62da5ec5ba4c32e61f0f6d9e61920 content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: rabualia date_created: 2021-11-22T14:48:34Z date_updated: 2022-12-20T23:30:06Z embargo_to: open_access file_id: '10332' file_name: AbualiaPhDthesisfinalv3.docx file_size: 62841883 relation: source_file file_date_updated: 2022-12-20T23:30:06Z has_accepted_license: '1' language: - iso: eng month: '11' oa: 1 oa_version: Published Version page: '139' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '9010' relation: part_of_dissertation status: public - id: '9913' relation: part_of_dissertation status: public - id: '47' relation: part_of_dissertation status: public status: public supervisor: - first_name: Eva full_name: Benková, Eva id: 38F4F166-F248-11E8-B48F-1D18A9856A87 last_name: Benková orcid: 0000-0002-8510-9739 title: Role of hormones in nitrate regulated growth tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10307' abstract: - lang: eng text: Bacteria-host interactions represent a continuous trade-off between benefit and risk. Thus, the host immune response is faced with a non-trivial problem – accommodate beneficial commensals and remove harmful pathogens. This is especially difficult as molecular patterns, such as lipopolysaccharide or specific surface organelles such as pili, are conserved in both, commensal and pathogenic bacteria. Type 1 pili, tightly regulated by phase variation, are considered an important virulence factor of pathogenic bacteria as they facilitate invasion into host cells. While invasion represents a de facto passive mechanism for pathogens to escape the host immune response, we demonstrate a fundamental role of type 1 pili as active modulators of the innate and adaptive immune response. acknowledged_ssus: - _id: LifeSc - _id: Bio - _id: PreCl - _id: EM-Fac alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Kathrin full_name: Tomasek, Kathrin id: 3AEC8556-F248-11E8-B48F-1D18A9856A87 last_name: Tomasek orcid: 0000-0003-3768-877X citation: ama: Tomasek K. Pathogenic Escherichia coli hijack the host immune response. 2021. doi:10.15479/at:ista:10307 apa: Tomasek, K. (2021). Pathogenic Escherichia coli hijack the host immune response. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10307 chicago: Tomasek, Kathrin. “Pathogenic Escherichia Coli Hijack the Host Immune Response.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10307. ieee: K. Tomasek, “Pathogenic Escherichia coli hijack the host immune response,” Institute of Science and Technology Austria, 2021. ista: Tomasek K. 2021. Pathogenic Escherichia coli hijack the host immune response. Institute of Science and Technology Austria. mla: Tomasek, Kathrin. Pathogenic Escherichia Coli Hijack the Host Immune Response. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10307. short: K. Tomasek, Pathogenic Escherichia Coli Hijack the Host Immune Response, Institute of Science and Technology Austria, 2021. date_created: 2021-11-18T15:05:06Z date_published: 2021-11-18T00:00:00Z date_updated: 2023-09-07T13:34:38Z day: '18' ddc: - '570' degree_awarded: PhD department: - _id: MiSi - _id: CaGu - _id: GradSch doi: 10.15479/at:ista:10307 file: - access_level: open_access checksum: b39c9e0ef18d0484d537a67551effd02 content_type: application/pdf creator: ktomasek date_created: 2021-11-18T15:07:31Z date_updated: 2022-12-20T23:30:05Z embargo: 2022-11-18 file_id: '10308' file_name: ThesisTomasekKathrin.pdf file_size: 13266088 relation: main_file - access_level: closed checksum: c0c440ee9e5ef1102a518a4f9f023e7c content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: ktomasek date_created: 2021-11-18T15:07:46Z date_updated: 2022-12-20T23:30:05Z embargo_to: open_access file_id: '10309' file_name: ThesisTomasekKathrin.docx file_size: 7539509 relation: source_file file_date_updated: 2022-12-20T23:30:05Z has_accepted_license: '1' language: - iso: eng month: '11' oa: 1 oa_version: Published Version page: '73' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '10316' relation: part_of_dissertation status: public status: public supervisor: - first_name: Michael K full_name: Sixt, Michael K id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87 last_name: Sixt orcid: 0000-0002-4561-241X - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 title: Pathogenic Escherichia coli hijack the host immune response type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10422' abstract: - lang: eng text: Those who aim to devise new materials with desirable properties usually examine present methods first. However, they will find out that some approaches can exist only conceptually without high chances to become practically useful. It seems that a numerical technique called automatic differentiation together with increasing supply of computational accelerators will soon shift many methods of the material design from the category ”unimaginable” to the category ”expensive but possible”. Approach we suggest is not an exception. Our overall goal is to have an efficient and generalizable approach allowing to solve inverse design problems. In this thesis we scratch its surface. We consider jammed systems of identical particles. And ask ourselves how the shape of those particles (or the parameters codifying it) may affect mechanical properties of the system. An indispensable part of reaching the answer is an appropriate particle parametrization. We come up with a simple, yet generalizable and purposeful scheme for it. Using our generalizable shape parameterization, we simulate the formation of a solid composed of pentagonal-like particles and measure anisotropy in the resulting elastic response. Through automatic differentiation techniques, we directly connect the shape parameters with the elastic response. Interestingly, for our system we find that less isotropic particles lead to a more isotropic elastic response. Together with other results known about our method it seems that it can be successfully generalized for different inverse design problems. alternative_title: - ISTA Master's Thesis article_processing_charge: No author: - first_name: Anton full_name: Piankov, Anton id: 865E3C26-AA8C-11E9-A409-C4C4E5697425 last_name: Piankov citation: ama: Piankov A. Towards designer materials using customizable particle shape. 2021. doi:10.15479/at:ista:10422 apa: Piankov, A. (2021). Towards designer materials using customizable particle shape. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10422 chicago: Piankov, Anton. “Towards Designer Materials Using Customizable Particle Shape.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10422. ieee: A. Piankov, “Towards designer materials using customizable particle shape,” Institute of Science and Technology Austria, 2021. ista: Piankov A. 2021. Towards designer materials using customizable particle shape. Institute of Science and Technology Austria. mla: Piankov, Anton. Towards Designer Materials Using Customizable Particle Shape. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10422. short: A. Piankov, Towards Designer Materials Using Customizable Particle Shape, Institute of Science and Technology Austria, 2021. date_created: 2021-12-07T10:48:06Z date_published: 2021-12-07T00:00:00Z date_updated: 2023-09-07T13:34:12Z day: '07' ddc: - '530' degree_awarded: MS department: - _id: GradSch - _id: CaGo doi: 10.15479/at:ista:10422 file: - access_level: closed checksum: 114e8f4b2c002c6c352416c12de2c695 content_type: application/x-zip-compressed creator: cchlebak date_created: 2021-12-07T11:13:52Z date_updated: 2022-03-10T12:10:25Z file_id: '10424' file_name: Thesis.zip file_size: 394018 relation: source_file - access_level: closed checksum: cd15ae991ced352a9959815f794e657c content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: cchlebak date_created: 2021-12-07T11:14:01Z date_updated: 2022-03-10T12:10:25Z file_id: '10425' file_name: Preliminary_pages_Piankov.docx file_size: 47638 relation: source_file - access_level: open_access checksum: e6899c798b75ba42fab9822bce309050 content_type: application/pdf creator: cchlebak date_created: 2021-12-07T11:20:35Z date_updated: 2021-12-07T11:20:35Z file_id: '10426' file_name: 2021_Piankov_combined.pdf file_size: 484965 relation: main_file success: 1 file_date_updated: 2022-03-10T12:10:25Z has_accepted_license: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version publication_identifier: issn: - 2791-4585 publication_status: published publisher: Institute of Science and Technology Austria status: public supervisor: - first_name: Carl Peter full_name: Goodrich, Carl Peter id: EB352CD2-F68A-11E9-89C5-A432E6697425 last_name: Goodrich orcid: 0000-0002-1307-5074 title: Towards designer materials using customizable particle shape type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10429' abstract: - lang: eng text: "The scalability of concurrent data structures and distributed algorithms strongly depends on\r\nreducing the contention for shared resources and the costs of synchronization and communication. We show how such cost reductions can be attained by relaxing the strict consistency conditions required by sequential implementations. In the first part of the thesis, we consider relaxation in the context of concurrent data structures. Specifically, in data structures \r\nsuch as priority queues, imposing strong semantics renders scalability impossible, since a correct implementation of the remove operation should return only the element with highest priority. Intuitively, attempting to invoke remove operations concurrently creates a race condition. This bottleneck can be circumvented by relaxing semantics of the affected data structure, thus allowing removal of the elements which are no longer required to have the highest priority. We prove that the randomized implementations of relaxed data structures provide provable guarantees on the priority of the removed elements even under concurrency. Additionally, we show that in some cases the relaxed data structures can be used to scale the classical algorithms which are usually implemented with the exact ones. In the second part, we study parallel variants of the stochastic gradient descent (SGD) algorithm, which distribute computation among the multiple processors, thus reducing the running time. Unfortunately, in order for standard parallel SGD to succeed, each processor has to maintain a local copy of the necessary model parameter, which is identical to the local copies of other processors; the overheads from this perfect consistency in terms of communication and synchronization can negate the speedup gained by distributing the computation. We show that the consistency conditions required by SGD can be relaxed, allowing the algorithm to be more flexible in terms of tolerating quantized communication, asynchrony, or even crash faults, while its convergence remains asymptotically the same." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Giorgi full_name: Nadiradze, Giorgi id: 3279A00C-F248-11E8-B48F-1D18A9856A87 last_name: Nadiradze orcid: 0000-0001-5634-0731 citation: ama: Nadiradze G. On achieving scalability through relaxation. 2021. doi:10.15479/at:ista:10429 apa: Nadiradze, G. (2021). On achieving scalability through relaxation. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10429 chicago: Nadiradze, Giorgi. “On Achieving Scalability through Relaxation.” Institute of Science and Technology Austria, 2021. https://doi.org/10.15479/at:ista:10429. ieee: G. Nadiradze, “On achieving scalability through relaxation,” Institute of Science and Technology Austria, 2021. ista: Nadiradze G. 2021. On achieving scalability through relaxation. Institute of Science and Technology Austria. mla: Nadiradze, Giorgi. On Achieving Scalability through Relaxation. Institute of Science and Technology Austria, 2021, doi:10.15479/at:ista:10429. short: G. Nadiradze, On Achieving Scalability through Relaxation, Institute of Science and Technology Austria, 2021. date_created: 2021-12-08T21:52:28Z date_published: 2021-12-09T00:00:00Z date_updated: 2023-10-17T11:48:55Z day: '09' ddc: - '000' degree_awarded: PhD department: - _id: GradSch - _id: DaAl doi: 10.15479/at:ista:10429 ec_funded: 1 file: - access_level: open_access checksum: 6bf14e9a523387328f016c0689f5e10e content_type: application/pdf creator: gnadirad date_created: 2021-12-09T17:47:49Z date_updated: 2021-12-09T17:47:49Z file_id: '10436' file_name: Thesis_Final_09_12_2021.pdf file_size: 2370859 relation: main_file success: 1 - access_level: closed checksum: 914d6c5ca86bd0add471971a8f4c4341 content_type: application/zip creator: gnadirad date_created: 2021-12-09T17:47:49Z date_updated: 2022-03-28T12:55:12Z file_id: '10437' file_name: Thesis_Final_09_12_2021.zip file_size: 2596924 relation: source_file file_date_updated: 2022-03-28T12:55:12Z has_accepted_license: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: '132' project: - _id: 268A44D6-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '805223' name: Elastic Coordination for Scalable Machine Learning publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '10432' relation: part_of_dissertation status: public - id: '6673' relation: part_of_dissertation status: public - id: '5965' relation: part_of_dissertation status: public - id: '10435' relation: part_of_dissertation status: public status: public supervisor: - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X title: On achieving scalability through relaxation type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2021' ... --- _id: '10635' abstract: - lang: eng text: The brain efficiently performs nonlinear computations through its intricate networks of spiking neurons, but how this is done remains elusive. While nonlinear computations can be implemented successfully in spiking neural networks, this requires supervised training and the resulting connectivity can be hard to interpret. In contrast, the required connectivity for any computation in the form of a linear dynamical system can be directly derived and understood with the spike coding network (SCN) framework. These networks also have biologically realistic activity patterns and are highly robust to cell death. Here we extend the SCN framework to directly implement any polynomial dynamical system, without the need for training. This results in networks requiring a mix of synapse types (fast, slow, and multiplicative), which we term multiplicative spike coding networks (mSCNs). Using mSCNs, we demonstrate how to directly derive the required connectivity for several nonlinear dynamical systems. We also show how to carry out higher-order polynomials with coupled networks that use only pair-wise multiplicative synapses, and provide expected numbers of connections for each synapse type. Overall, our work demonstrates a novel method for implementing nonlinear computations in spiking neural networks, while keeping the attractive features of standard SCNs (robustness, realistic activity patterns, and interpretable connectivity). Finally, we discuss the biological plausibility of our approach, and how the high accuracy and robustness of the approach may be of interest for neuromorphic computing. acknowledgement: "A preprint version of this article has been peer-reviewed and recommended by Peer Community In Neuroscience (DOI link to the recommendation: https://doi.org/10.24072/pci.cneuro.100003).\r\nWe thank Christian Machens and Nuno Calaim for useful discussions on the project. This report\r\ncame out of a collaboration started at the CAJAL Advanced Neuroscience Training Programme in\r\nComputational Neuroscience in Lisbon, Portugal, during the 2019 summer. The authors would\r\nlike to thank the participants, TAs, lecturers, and organizers of the summer school. SWK was\r\nsupported by the Simons Collaboration on the Global Brain (543009). WFP was supported by\r\nFCT (032077). MN was supported by European Union Horizon 2020 (665385).\r\n" article_number: e68 article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Michele full_name: Nardin, Michele id: 30BD0376-F248-11E8-B48F-1D18A9856A87 last_name: Nardin orcid: 0000-0001-8849-6570 - first_name: James W. full_name: Phillips, James W. last_name: Phillips - first_name: William F. full_name: Podlaski, William F. last_name: Podlaski - first_name: Sander W. full_name: Keemink, Sander W. last_name: Keemink citation: ama: Nardin M, Phillips JW, Podlaski WF, Keemink SW. Nonlinear computations in spiking neural networks through multiplicative synapses. Peer Community Journal. 2021;1. doi:10.24072/pcjournal.69 apa: Nardin, M., Phillips, J. W., Podlaski, W. F., & Keemink, S. W. (2021). Nonlinear computations in spiking neural networks through multiplicative synapses. Peer Community Journal. Centre Mersenne ; Peer Community In. https://doi.org/10.24072/pcjournal.69 chicago: Nardin, Michele, James W. Phillips, William F. Podlaski, and Sander W. Keemink. “Nonlinear Computations in Spiking Neural Networks through Multiplicative Synapses.” Peer Community Journal. Centre Mersenne ; Peer Community In, 2021. https://doi.org/10.24072/pcjournal.69. ieee: M. Nardin, J. W. Phillips, W. F. Podlaski, and S. W. Keemink, “Nonlinear computations in spiking neural networks through multiplicative synapses,” Peer Community Journal, vol. 1. Centre Mersenne ; Peer Community In, 2021. ista: Nardin M, Phillips JW, Podlaski WF, Keemink SW. 2021. Nonlinear computations in spiking neural networks through multiplicative synapses. Peer Community Journal. 1, e68. mla: Nardin, Michele, et al. “Nonlinear Computations in Spiking Neural Networks through Multiplicative Synapses.” Peer Community Journal, vol. 1, e68, Centre Mersenne ; Peer Community In, 2021, doi:10.24072/pcjournal.69. short: M. Nardin, J.W. Phillips, W.F. Podlaski, S.W. Keemink, Peer Community Journal 1 (2021). date_created: 2022-01-17T11:12:40Z date_published: 2021-12-15T00:00:00Z date_updated: 2022-01-17T13:30:01Z day: '15' ddc: - '519' department: - _id: GradSch - _id: JoCs doi: 10.24072/pcjournal.69 ec_funded: 1 external_id: arxiv: - '2009.03857' file: - access_level: open_access checksum: cd9af6b331918608f2e3d1c7940cbf4f content_type: application/pdf creator: mnardin date_created: 2022-01-17T11:15:26Z date_updated: 2022-01-17T11:15:26Z file_id: '10636' file_name: 10_24072_pcjournal_69.pdf file_size: 3311494 relation: main_file success: 1 file_date_updated: 2022-01-17T11:15:26Z has_accepted_license: '1' intvolume: ' 1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: Peer Community Journal publication_identifier: eissn: - 2804-3871 publication_status: published publisher: Centre Mersenne ; Peer Community In quality_controlled: '1' status: public title: Nonlinear computations in spiking neural networks through multiplicative synapses tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 1 year: '2021' ... --- _id: '10665' abstract: - lang: eng text: "Formal verification of neural networks is an active topic of research, and recent advances have significantly increased the size of the networks that verification tools can handle. However, most methods are designed for verification of an idealized model of the actual network which works over real arithmetic and ignores rounding imprecisions. This idealization is in stark contrast to network quantization, which is a technique that trades numerical precision for computational efficiency and is, therefore, often applied in practice. Neglecting rounding errors of such low-bit quantized neural networks has been shown to lead to wrong conclusions about the network’s correctness. Thus, the desired approach for verifying quantized neural networks would be one that takes these rounding errors\r\ninto account. In this paper, we show that verifying the bitexact implementation of quantized neural networks with bitvector specifications is PSPACE-hard, even though verifying idealized real-valued networks and satisfiability of bit-vector specifications alone are each in NP. Furthermore, we explore several practical heuristics toward closing the complexity gap between idealized and bit-exact verification. In particular, we propose three techniques for making SMT-based verification of quantized neural networks more scalable. Our experiments demonstrate that our proposed methods allow a speedup of up to three orders of magnitude over existing approaches." acknowledgement: "This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein\r\nAward), ERC CoG 863818 (FoRM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.\r\n" alternative_title: - Technical Tracks article_processing_charge: No arxiv: 1 author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 citation: ama: 'Henzinger TA, Lechner M, Zikelic D. Scalable verification of quantized neural networks. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. AAAI Press; 2021:3787-3795.' apa: 'Henzinger, T. A., Lechner, M., & Zikelic, D. (2021). Scalable verification of quantized neural networks. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 3787–3795). Virtual: AAAI Press.' chicago: Henzinger, Thomas A, Mathias Lechner, and Dorde Zikelic. “Scalable Verification of Quantized Neural Networks.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:3787–95. AAAI Press, 2021. ieee: T. A. Henzinger, M. Lechner, and D. Zikelic, “Scalable verification of quantized neural networks,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 5A, pp. 3787–3795. ista: 'Henzinger TA, Lechner M, Zikelic D. 2021. Scalable verification of quantized neural networks. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 3787–3795.' mla: Henzinger, Thomas A., et al. “Scalable Verification of Quantized Neural Networks.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 5A, AAAI Press, 2021, pp. 3787–95. short: T.A. Henzinger, M. Lechner, D. Zikelic, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 3787–3795. conference: end_date: 2021-02-09 location: Virtual name: 'AAAI: Association for the Advancement of Artificial Intelligence' start_date: 2021-02-02 date_created: 2022-01-25T15:15:02Z date_published: 2021-05-28T00:00:00Z date_updated: 2025-07-14T09:10:11Z day: '28' ddc: - '000' department: - _id: GradSch - _id: ToHe ec_funded: 1 external_id: arxiv: - '2012.08185' file: - access_level: open_access checksum: 2bc8155b2526a70fba5b7301bc89dbd1 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:41:16Z date_updated: 2022-01-26T07:41:16Z file_id: '10684' file_name: 16496-Article Text-19990-1-2-20210518 (1).pdf file_size: 137235 relation: main_file success: 1 file_date_updated: 2022-01-26T07:41:16Z has_accepted_license: '1' intvolume: ' 35' issue: 5A language: - iso: eng main_file_link: - open_access: '1' url: https://ojs.aaai.org/index.php/AAAI/article/view/16496 month: '05' oa: 1 oa_version: Published Version page: 3787-3795 project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication: Proceedings of the AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 isbn: - 978-1-57735-866-4 issn: - 2159-5399 publication_status: published publisher: AAAI Press quality_controlled: '1' related_material: record: - id: '11362' relation: dissertation_contains status: public scopus_import: '1' status: public title: Scalable verification of quantized neural networks type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2021' ... --- _id: '10666' abstract: - lang: eng text: Adversarial training is an effective method to train deep learning models that are resilient to norm-bounded perturbations, with the cost of nominal performance drop. While adversarial training appears to enhance the robustness and safety of a deep model deployed in open-world decision-critical applications, counterintuitively, it induces undesired behaviors in robot learning settings. In this paper, we show theoretically and experimentally that neural controllers obtained via adversarial training are subjected to three types of defects, namely transient, systematic, and conditional errors. We first generalize adversarial training to a safety-domain optimization scheme allowing for more generic specifications. We then prove that such a learning process tends to cause certain error profiles. We support our theoretical results by a thorough experimental safety analysis in a robot-learning task. Our results suggest that adversarial training is not yet ready for robot learning. acknowledgement: M.L. and T.A.H. are supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. are supported by Boeing and R.G. by Horizon-2020 ECSEL Project grant no. 783163 (iDev40). article_processing_charge: No arxiv: 1 author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Radu full_name: Grosu, Radu last_name: Grosu - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. Adversarial training is not ready for robot learning. In: 2021 IEEE International Conference on Robotics and Automation. ICRA. ; 2021:4140-4147. doi:10.1109/ICRA48506.2021.9561036' apa: Lechner, M., Hasani, R., Grosu, R., Rus, D., & Henzinger, T. A. (2021). Adversarial training is not ready for robot learning. In 2021 IEEE International Conference on Robotics and Automation (pp. 4140–4147). Xi’an, China. https://doi.org/10.1109/ICRA48506.2021.9561036 chicago: Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger. “Adversarial Training Is Not Ready for Robot Learning.” In 2021 IEEE International Conference on Robotics and Automation, 4140–47. ICRA, 2021. https://doi.org/10.1109/ICRA48506.2021.9561036. ieee: M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial training is not ready for robot learning,” in 2021 IEEE International Conference on Robotics and Automation, Xi’an, China, 2021, pp. 4140–4147. ista: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. 2021. Adversarial training is not ready for robot learning. 2021 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and AutomationICRA, 4140–4147.' mla: Lechner, Mathias, et al. “Adversarial Training Is Not Ready for Robot Learning.” 2021 IEEE International Conference on Robotics and Automation, 2021, pp. 4140–47, doi:10.1109/ICRA48506.2021.9561036. short: M. Lechner, R. Hasani, R. Grosu, D. Rus, T.A. Henzinger, in:, 2021 IEEE International Conference on Robotics and Automation, 2021, pp. 4140–4147. conference: end_date: 2021-06-05 location: Xi'an, China name: 'ICRA: International Conference on Robotics and Automation' start_date: 2021-05-30 date_created: 2022-01-25T15:44:54Z date_published: 2021-01-01T00:00:00Z date_updated: 2023-08-17T06:58:38Z ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1109/ICRA48506.2021.9561036 external_id: arxiv: - '2103.08187' isi: - '000765738803040' has_accepted_license: '1' isi: 1 language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/3.0/ main_file_link: - open_access: '1' url: https://arxiv.org/abs/2103.08187 oa: 1 oa_version: None page: 4140-4147 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 2021 IEEE International Conference on Robotics and Automation publication_identifier: eisbn: - 978-1-7281-9077-8 eissn: - 2577-087X isbn: - 978-1-7281-9078-5 issn: - 1050-4729 publication_status: published quality_controlled: '1' related_material: record: - id: '11362' relation: dissertation_contains status: public series_title: ICRA status: public title: Adversarial training is not ready for robot learning tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 year: '2021' ... --- _id: '10667' abstract: - lang: eng text: Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network's prediction. We consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with infinite time horizon systems. Compared to the existing sampling-based approaches, which are inapplicable to the infinite time horizon setting, we train a separate deterministic neural network that serves as an infinite time horizon safety certificate. In particular, we show that the certificate network guarantees the safety of the system over a subset of the BNN weight posterior's support. Our method first computes a safe weight set and then alters the BNN's weight posterior to reject samples outside this set. Moreover, we show how to extend our approach to a safe-exploration reinforcement learning setting, in order to avoid unsafe trajectories during the training of the policy. We evaluate our approach on a series of reinforcement learning benchmarks, including non-Lyapunovian safety specifications. acknowledgement: This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award), ERC CoG 863818 (FoRM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. alternative_title: - ' Advances in Neural Information Processing Systems' article_processing_charge: No arxiv: 1 author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ðorđe full_name: Žikelić, Ðorđe last_name: Žikelić - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. Infinite time horizon safety of Bayesian neural networks. In: 35th Conference on Neural Information Processing Systems. ; 2021. doi:10.48550/arXiv.2111.03165' apa: Lechner, M., Žikelić, Ð., Chatterjee, K., & Henzinger, T. A. (2021). Infinite time horizon safety of Bayesian neural networks. In 35th Conference on Neural Information Processing Systems. Virtual. https://doi.org/10.48550/arXiv.2111.03165 chicago: Lechner, Mathias, Ðorđe Žikelić, Krishnendu Chatterjee, and Thomas A Henzinger. “Infinite Time Horizon Safety of Bayesian Neural Networks.” In 35th Conference on Neural Information Processing Systems, 2021. https://doi.org/10.48550/arXiv.2111.03165. ieee: M. Lechner, Ð. Žikelić, K. Chatterjee, and T. A. Henzinger, “Infinite time horizon safety of Bayesian neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, 2021. ista: 'Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. 2021. Infinite time horizon safety of Bayesian neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, .' mla: Lechner, Mathias, et al. “Infinite Time Horizon Safety of Bayesian Neural Networks.” 35th Conference on Neural Information Processing Systems, 2021, doi:10.48550/arXiv.2111.03165. short: M. Lechner, Ð. Žikelić, K. Chatterjee, T.A. Henzinger, in:, 35th Conference on Neural Information Processing Systems, 2021. conference: end_date: 2021-12-10 location: Virtual name: 'NeurIPS: Neural Information Processing Systems' start_date: 2021-12-06 date_created: 2022-01-25T15:45:58Z date_published: 2021-12-01T00:00:00Z date_updated: 2025-07-14T09:10:12Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe - _id: KrCh doi: 10.48550/arXiv.2111.03165 ec_funded: 1 external_id: arxiv: - '2111.03165' file: - access_level: open_access checksum: 0fc0f852525c10dda9cc9ffea07fb4e4 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:39:59Z date_updated: 2022-01-26T07:39:59Z file_id: '10682' file_name: infinite_time_horizon_safety_o.pdf file_size: 452492 relation: main_file success: 1 file_date_updated: 2022-01-26T07:39:59Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://proceedings.neurips.cc/paper/2021/hash/544defa9fddff50c53b71c43e0da72be-Abstract.html month: '12' oa: 1 oa_version: Published Version project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 35th Conference on Neural Information Processing Systems publication_status: published quality_controlled: '1' related_material: record: - id: '11362' relation: dissertation_contains status: public status: public title: Infinite time horizon safety of Bayesian neural networks tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '10668' abstract: - lang: eng text: 'Robustness to variations in lighting conditions is a key objective for any deep vision system. To this end, our paper extends the receptive field of convolutional neural networks with two residual components, ubiquitous in the visual processing system of vertebrates: On-center and off-center pathways, with an excitatory center and inhibitory surround; OOCS for short. The On-center pathway is excited by the presence of a light stimulus in its center, but not in its surround, whereas the Off-center pathway is excited by the absence of a light stimulus in its center, but not in its surround. We design OOCS pathways via a difference of Gaussians, with their variance computed analytically from the size of the receptive fields. OOCS pathways complement each other in their response to light stimuli, ensuring this way a strong edge-detection capability, and as a result an accurate and robust inference under challenging lighting conditions. We provide extensive empirical evidence showing that networks supplied with OOCS pathways gain accuracy and illumination-robustness from the novel edge representation, compared to other baselines.' acknowledgement: Z.B. is supported by the Doctoral College Resilient Embedded Systems, which is run jointly by the TU Wien’s Faculty of Informatics and the UAS Technikum Wien. R.G. is partially supported by the Horizon 2020 Era-Permed project Persorad, and ECSEL Project grant no. 783163 (iDev40). R.H and D.R were partially supported by Boeing and MIT. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). alternative_title: - PMLR article_processing_charge: No author: - first_name: Zahra full_name: Babaiee, Zahra last_name: Babaiee - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. On-off center-surround receptive fields for accurate and robust image classification. In: Proceedings of the 38th International Conference on Machine Learning. Vol 139. ML Research Press; 2021:478-489.' apa: 'Babaiee, Z., Hasani, R., Lechner, M., Rus, D., & Grosu, R. (2021). On-off center-surround receptive fields for accurate and robust image classification. In Proceedings of the 38th International Conference on Machine Learning (Vol. 139, pp. 478–489). Virtual: ML Research Press.' chicago: Babaiee, Zahra, Ramin Hasani, Mathias Lechner, Daniela Rus, and Radu Grosu. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” In Proceedings of the 38th International Conference on Machine Learning, 139:478–89. ML Research Press, 2021. ieee: Z. Babaiee, R. Hasani, M. Lechner, D. Rus, and R. Grosu, “On-off center-surround receptive fields for accurate and robust image classification,” in Proceedings of the 38th International Conference on Machine Learning, Virtual, 2021, vol. 139, pp. 478–489. ista: 'Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. 2021. On-off center-surround receptive fields for accurate and robust image classification. Proceedings of the 38th International Conference on Machine Learning. ML: Machine Learning, PMLR, vol. 139, 478–489.' mla: Babaiee, Zahra, et al. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” Proceedings of the 38th International Conference on Machine Learning, vol. 139, ML Research Press, 2021, pp. 478–89. short: Z. Babaiee, R. Hasani, M. Lechner, D. Rus, R. Grosu, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 478–489. conference: end_date: 2021-07-24 location: Virtual name: 'ML: Machine Learning' start_date: 2021-07-18 date_created: 2022-01-25T15:46:33Z date_published: 2021-07-01T00:00:00Z date_updated: 2022-05-04T15:02:27Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe file: - access_level: open_access checksum: d30eae62561bb517d9f978437d7677db content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:38:32Z date_updated: 2022-01-26T07:38:32Z file_id: '10681' file_name: babaiee21a.pdf file_size: 4246561 relation: main_file success: 1 file_date_updated: 2022-01-26T07:38:32Z has_accepted_license: '1' intvolume: ' 139' language: - iso: eng main_file_link: - open_access: '1' url: https://proceedings.mlr.press/v139/babaiee21a month: '07' oa: 1 oa_version: Published Version page: 478-489 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the 38th International Conference on Machine Learning publication_identifier: issn: - 2640-3498 publication_status: published publisher: ML Research Press quality_controlled: '1' status: public title: On-off center-surround receptive fields for accurate and robust image classification tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87 volume: 139 year: '2021' ... --- _id: '10669' abstract: - lang: eng text: "We show that Neural ODEs, an emerging class of timecontinuous neural networks, can be verified by solving a set of global-optimization problems. For this purpose, we introduce Stochastic Lagrangian Reachability (SLR), an\r\nabstraction-based technique for constructing a tight Reachtube (an over-approximation of the set of reachable states\r\nover a given time-horizon), and provide stochastic guarantees in the form of confidence intervals for the Reachtube bounds. SLR inherently avoids the infamous wrapping effect (accumulation of over-approximation errors) by performing local optimization steps to expand safe regions instead of repeatedly forward-propagating them as is done by deterministic reachability methods. To enable fast local optimizations, we introduce a novel forward-mode adjoint sensitivity method to compute gradients without the need for backpropagation. Finally, we establish asymptotic and non-asymptotic convergence rates for SLR." acknowledgement: "The authors would like to thank the reviewers for their insightful comments. RH and RG were partially supported by\r\nHorizon-2020 ECSEL Project grant No. 783163 (iDev40). RH was partially supported by Boeing. ML was supported\r\nin part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). SG was funded by FWF\r\nproject W1255-N23. JC was partially supported by NAWA Polish Returns grant PPN/PPO/2018/1/00029. SS was supported by NSF awards DCL-2040599, CCF-1918225, and CPS-1446832.\r\n" alternative_title: - Technical Tracks article_processing_charge: No arxiv: 1 author: - first_name: Sophie full_name: Grunbacher, Sophie last_name: Grunbacher - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Jacek full_name: Cyranka, Jacek last_name: Cyranka - first_name: Scott A full_name: Smolka, Scott A last_name: Smolka - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. On the verification of neural ODEs with stochastic guarantees. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. AAAI Press; 2021:11525-11535.' apa: 'Grunbacher, S., Hasani, R., Lechner, M., Cyranka, J., Smolka, S. A., & Grosu, R. (2021). On the verification of neural ODEs with stochastic guarantees. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 11525–11535). Virtual: AAAI Press.' chicago: Grunbacher, Sophie, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A Smolka, and Radu Grosu. “On the Verification of Neural ODEs with Stochastic Guarantees.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:11525–35. AAAI Press, 2021. ieee: S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S. A. Smolka, and R. Grosu, “On the verification of neural ODEs with stochastic guarantees,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 13, pp. 11525–11535. ista: 'Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. 2021. On the verification of neural ODEs with stochastic guarantees. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 11525–11535.' mla: Grunbacher, Sophie, et al. “On the Verification of Neural ODEs with Stochastic Guarantees.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 13, AAAI Press, 2021, pp. 11525–35. short: S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S.A. Smolka, R. Grosu, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 11525–11535. conference: end_date: 2021-02-09 location: Virtual name: 'AAAI: Association for the Advancement of Artificial Intelligence' start_date: 2021-02-02 date_created: 2022-01-25T15:47:20Z date_published: 2021-05-28T00:00:00Z date_updated: 2022-05-24T06:33:14Z day: '28' ddc: - '000' department: - _id: GradSch - _id: ToHe external_id: arxiv: - '2012.08863' file: - access_level: open_access checksum: 468d07041e282a1d46ffdae92f709630 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:38:08Z date_updated: 2022-01-26T07:38:08Z file_id: '10680' file_name: 17372-Article Text-20866-1-2-20210518.pdf file_size: 286906 relation: main_file success: 1 file_date_updated: 2022-01-26T07:38:08Z has_accepted_license: '1' intvolume: ' 35' issue: '13' language: - iso: eng main_file_link: - open_access: '1' url: https://ojs.aaai.org/index.php/AAAI/article/view/17372 month: '05' oa: 1 oa_version: Published Version page: 11525-11535 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 isbn: - 978-1-57735-866-4 issn: - 2159-5399 publication_status: published publisher: AAAI Press quality_controlled: '1' status: public title: On the verification of neural ODEs with stochastic guarantees type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2021' ... --- _id: '10670' abstract: - lang: eng text: "Imitation learning enables high-fidelity, vision-based learning of policies within rich, photorealistic environments. However, such techniques often rely on traditional discrete-time neural models and face difficulties in generalizing to domain shifts by failing to account for the causal relationships between the agent and the environment. In this paper, we propose a theoretical and experimental framework for learning causal representations using continuous-time neural networks, specifically over their discrete-time counterparts. We evaluate our method in the context of visual-control learning of drones over a series of complex tasks, ranging from short- and long-term navigation, to chasing static and dynamic objects through photorealistic environments. Our results demonstrate that causal continuous-time\r\ndeep models can perform robust navigation tasks, where advanced recurrent models fail. These models learn complex causal control representations directly from raw visual inputs and scale to solve a variety of tasks using imitation learning." acknowledgement: "C.V., R.H. A.A. and D.R. are partially supported by Boeing and MIT. A.A. is supported by the National Science Foundation (NSF) Graduate Research Fellowship Program. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). Research was sponsored by the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors\r\nand should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.\r\n" alternative_title: - ' Advances in Neural Information Processing Systems' article_processing_charge: No arxiv: 1 author: - first_name: Charles J full_name: Vorbach, Charles J last_name: Vorbach - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Daniela full_name: Rus, Daniela last_name: Rus citation: ama: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. Causal navigation by continuous-time neural networks. In: 35th Conference on Neural Information Processing Systems. ; 2021.' apa: Vorbach, C. J., Hasani, R., Amini, A., Lechner, M., & Rus, D. (2021). Causal navigation by continuous-time neural networks. In 35th Conference on Neural Information Processing Systems. Virtual. chicago: Vorbach, Charles J, Ramin Hasani, Alexander Amini, Mathias Lechner, and Daniela Rus. “Causal Navigation by Continuous-Time Neural Networks.” In 35th Conference on Neural Information Processing Systems, 2021. ieee: C. J. Vorbach, R. Hasani, A. Amini, M. Lechner, and D. Rus, “Causal navigation by continuous-time neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, 2021. ista: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. 2021. Causal navigation by continuous-time neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, .' mla: Vorbach, Charles J., et al. “Causal Navigation by Continuous-Time Neural Networks.” 35th Conference on Neural Information Processing Systems, 2021. short: C.J. Vorbach, R. Hasani, A. Amini, M. Lechner, D. Rus, in:, 35th Conference on Neural Information Processing Systems, 2021. conference: end_date: 2021-12-10 location: Virtual name: 'NeurIPS: Neural Information Processing Systems' start_date: 2021-12-06 date_created: 2022-01-25T15:47:50Z date_published: 2021-12-01T00:00:00Z date_updated: 2022-01-26T14:33:31Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe external_id: arxiv: - '2106.08314' file: - access_level: open_access checksum: be81f0ade174a8c9b2d4fe09590b2021 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:37:24Z date_updated: 2022-01-26T07:37:24Z file_id: '10679' file_name: NeurIPS-2021-causal-navigation-by-continuous-time-neural-networks-Paper.pdf file_size: 6841228 relation: main_file success: 1 file_date_updated: 2022-01-26T07:37:24Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://proceedings.neurips.cc/paper/2021/hash/67ba02d73c54f0b83c05507b7fb7267f-Abstract.html month: '12' oa: 1 oa_version: Published Version project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 35th Conference on Neural Information Processing Systems publication_status: published quality_controlled: '1' status: public title: Causal navigation by continuous-time neural networks tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ...