[{"article_processing_charge":"No","type":"research_data_reference","publisher":"Zenodo","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"main_file_link":[{"url":"https://doi.org/10.5281/zenodo.3271452","open_access":"1"}],"date_published":"2018-12-07T00:00:00Z","date_created":"2023-05-23T16:08:20Z","oa_version":"Published Version","citation":{"short":"E. Garriga, P. di Tommaso, C. Magis, I. Erb, L. Mansouri, A. Baltzis, H. Laayouni, F. Kondrashov, E. Floden, C. Notredame, (2018).","ista":"Garriga E, di Tommaso P, Magis C, Erb I, Mansouri L, Baltzis A, Laayouni H, Kondrashov F, Floden E, Notredame C. 2018. Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.2025846\">10.5281/ZENODO.2025846</a>.","ama":"Garriga E, di Tommaso P, Magis C, et al. Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method. 2018. doi:<a href=\"https://doi.org/10.5281/ZENODO.2025846\">10.5281/ZENODO.2025846</a>","ieee":"E. Garriga <i>et al.</i>, “Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method.” Zenodo, 2018.","apa":"Garriga, E., di Tommaso, P., Magis, C., Erb, I., Mansouri, L., Baltzis, A., … Notredame, C. (2018). Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.2025846\">https://doi.org/10.5281/ZENODO.2025846</a>","mla":"Garriga, Edgar, et al. <i>Fast and Accurate Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method</i>. Zenodo, 2018, doi:<a href=\"https://doi.org/10.5281/ZENODO.2025846\">10.5281/ZENODO.2025846</a>.","chicago":"Garriga, Edgar, Paolo di Tommaso, Cedrik Magis, Ionas Erb, Leila Mansouri, Athanasios Baltzis, Hafid Laayouni, Fyodor Kondrashov, Evan Floden, and Cedric Notredame. “Fast and Accurate Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method.” Zenodo, 2018. <a href=\"https://doi.org/10.5281/ZENODO.2025846\">https://doi.org/10.5281/ZENODO.2025846</a>."},"day":"07","department":[{"_id":"FyKo"}],"ddc":["570"],"month":"12","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","related_material":{"record":[{"id":"7181","status":"public","relation":"used_in_publication"}]},"status":"public","date_updated":"2023-09-06T14:32:51Z","abstract":[{"text":"This dataset contains a GitHub repository containing all the data, analysis, Nextflow workflows and Jupyter notebooks to replicate the manuscript titled \"Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method\".\r\nIt also contains the Multiple Sequence Alignments (MSAs) generated and well as the main figures and tables from the manuscript.\r\nThe repository is also available at GitHub (https://github.com/cbcrg/dpa-analysis) release `v1.2`.\r\nFor details on how to use the regressive alignment algorithm, see the T-Coffee software suite (https://github.com/cbcrg/tcoffee).","lang":"eng"}],"year":"2018","doi":"10.5281/ZENODO.2025846","oa":1,"title":"Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method","author":[{"last_name":"Garriga","full_name":"Garriga, Edgar","first_name":"Edgar"},{"full_name":"di Tommaso, Paolo","last_name":"di Tommaso","first_name":"Paolo"},{"full_name":"Magis, Cedrik","last_name":"Magis","first_name":"Cedrik"},{"first_name":"Ionas","full_name":"Erb, Ionas","last_name":"Erb"},{"first_name":"Leila","full_name":"Mansouri, Leila","last_name":"Mansouri"},{"last_name":"Baltzis","full_name":"Baltzis, Athanasios","first_name":"Athanasios"},{"full_name":"Laayouni, Hafid","last_name":"Laayouni","first_name":"Hafid"},{"first_name":"Fyodor","id":"44FDEF62-F248-11E8-B48F-1D18A9856A87","last_name":"Kondrashov","full_name":"Kondrashov, Fyodor","orcid":"0000-0001-8243-4694"},{"last_name":"Floden","full_name":"Floden, Evan","first_name":"Evan"},{"last_name":"Notredame","full_name":"Notredame, Cedric","first_name":"Cedric"}],"_id":"13059"},{"oa":1,"year":"2018","publication":"eLife","date_updated":"2024-02-21T13:45:12Z","related_material":{"record":[{"status":"public","relation":"popular_science","id":"5586"}]},"article_number":"e35684","article_type":"original","department":[{"_id":"BeVi"}],"publist_id":"7792","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","external_id":{"isi":["000441388200001"]},"date_published":"2018-08-13T00:00:00Z","date_created":"2018-12-11T11:44:47Z","scopus_import":"1","publisher":"eLife Sciences Publications","intvolume":"         7","isi":1,"quality_controlled":"1","type":"journal_article","language":[{"iso":"eng"}],"title":"Evolution of gene dosage on the Z-chromosome of schistosome parasites","author":[{"orcid":"0000-0002-8101-2518","id":"2C921A7A-F248-11E8-B48F-1D18A9856A87","first_name":"Marion A","full_name":"Picard, Marion A","last_name":"Picard"},{"first_name":"Celine","last_name":"Cosseau","full_name":"Cosseau, Celine"},{"full_name":"Ferré, Sabrina","last_name":"Ferré","first_name":"Sabrina"},{"first_name":"Thomas","full_name":"Quack, Thomas","last_name":"Quack"},{"first_name":"Christoph","last_name":"Grevelding","full_name":"Grevelding, Christoph"},{"full_name":"Couté, Yohann","last_name":"Couté","first_name":"Yohann"},{"id":"49E1C5C6-F248-11E8-B48F-1D18A9856A87","first_name":"Beatriz","full_name":"Vicoso, Beatriz","last_name":"Vicoso","orcid":"0000-0002-4579-8306"}],"_id":"131","abstract":[{"text":"XY systems usually show chromosome-wide compensation of X-linked genes, while in many ZW systems, compensation is restricted to a minority of dosage-sensitive genes. Why such differences arose is still unclear. Here, we combine comparative genomics, transcriptomics and proteomics to obtain a complete overview of the evolution of gene dosage on the Z-chromosome of Schistosoma parasites. We compare the Z-chromosome gene content of African (Schistosoma mansoni and S. haematobium) and Asian (S. japonicum) schistosomes and describe lineage-specific evolutionary strata. We use these to assess gene expression evolution following sex-linkage. The resulting patterns suggest a reduction in expression of Z-linked genes in females, combined with upregulation of the Z in both sexes, in line with the first step of Ohno’s classic model of dosage compensation evolution. Quantitative proteomics suggest that post-transcriptional mechanisms do not play a major role in balancing the expression of Z-linked genes. ","lang":"eng"}],"doi":"10.7554/eLife.35684","project":[{"grant_number":"P28842-B22","_id":"250ED89C-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Sex chromosome evolution under male- and female- heterogamety"}],"status":"public","publication_status":"published","acknowledgement":"We are grateful to Lu Dabing (Soochow University, Suzhou, China) for providing Schistosoma japonicum samples, to Ariana Macon (IST Austria) and Georgette Stovall (JLU Giessen) for technical assistance, to IT support at IST Austria for providing optimal environment to bioinformatic analyses, and to the Vicoso lab for comments on the manuscript.","citation":{"ista":"Picard MAL, Cosseau C, Ferré S, Quack T, Grevelding C, Couté Y, Vicoso B. 2018. Evolution of gene dosage on the Z-chromosome of schistosome parasites. eLife. 7, e35684.","short":"M.A.L. Picard, C. Cosseau, S. Ferré, T. Quack, C. Grevelding, Y. Couté, B. Vicoso, ELife 7 (2018).","ama":"Picard MAL, Cosseau C, Ferré S, et al. Evolution of gene dosage on the Z-chromosome of schistosome parasites. <i>eLife</i>. 2018;7. doi:<a href=\"https://doi.org/10.7554/eLife.35684\">10.7554/eLife.35684</a>","apa":"Picard, M. A. L., Cosseau, C., Ferré, S., Quack, T., Grevelding, C., Couté, Y., &#38; Vicoso, B. (2018). Evolution of gene dosage on the Z-chromosome of schistosome parasites. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/eLife.35684\">https://doi.org/10.7554/eLife.35684</a>","ieee":"M. A. L. Picard <i>et al.</i>, “Evolution of gene dosage on the Z-chromosome of schistosome parasites,” <i>eLife</i>, vol. 7. eLife Sciences Publications, 2018.","chicago":"Picard, Marion A L, Celine Cosseau, Sabrina Ferré, Thomas Quack, Christoph Grevelding, Yohann Couté, and Beatriz Vicoso. “Evolution of Gene Dosage on the Z-Chromosome of Schistosome Parasites.” <i>ELife</i>. eLife Sciences Publications, 2018. <a href=\"https://doi.org/10.7554/eLife.35684\">https://doi.org/10.7554/eLife.35684</a>.","mla":"Picard, Marion A. L., et al. “Evolution of Gene Dosage on the Z-Chromosome of Schistosome Parasites.” <i>ELife</i>, vol. 7, e35684, eLife Sciences Publications, 2018, doi:<a href=\"https://doi.org/10.7554/eLife.35684\">10.7554/eLife.35684</a>."},"day":"13","ddc":["570"],"file_date_updated":"2020-07-14T12:44:43Z","month":"08","oa_version":"Published Version","file":[{"date_created":"2018-12-17T11:55:05Z","file_id":"5695","date_updated":"2020-07-14T12:44:43Z","content_type":"application/pdf","checksum":"d6331d4385b1fffd6b47b45d5949d841","access_level":"open_access","creator":"dernst","file_size":3158125,"relation":"main_file","file_name":"2018_eLife_Picard.pdf"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"has_accepted_license":"1","article_processing_charge":"No","volume":7},{"day":"06","citation":{"chicago":"Sznurkowska, Magdalena, Edouard B Hannezo, Roberta Azzarelli, Steffen Rulands, Sonia Nestorowa, Christopher Hindley, Jennifer Nichols, et al. “Defining Lineage Potential and Fate Behavior of Precursors during Pancreas Development.” <i>Developmental Cell</i>. Cell Press, 2018. <a href=\"https://doi.org/10.1016/j.devcel.2018.06.028\">https://doi.org/10.1016/j.devcel.2018.06.028</a>.","mla":"Sznurkowska, Magdalena, et al. “Defining Lineage Potential and Fate Behavior of Precursors during Pancreas Development.” <i>Developmental Cell</i>, vol. 46, no. 3, Cell Press, 2018, pp. 360–75, doi:<a href=\"https://doi.org/10.1016/j.devcel.2018.06.028\">10.1016/j.devcel.2018.06.028</a>.","ama":"Sznurkowska M, Hannezo EB, Azzarelli R, et al. Defining lineage potential and fate behavior of precursors during pancreas development. <i>Developmental Cell</i>. 2018;46(3):360-375. doi:<a href=\"https://doi.org/10.1016/j.devcel.2018.06.028\">10.1016/j.devcel.2018.06.028</a>","short":"M. Sznurkowska, E.B. Hannezo, R. Azzarelli, S. Rulands, S. Nestorowa, C. Hindley, J. Nichols, B. Göttgens, M. Huch, A. Philpott, B. Simons, Developmental Cell 46 (2018) 360–375.","ista":"Sznurkowska M, Hannezo EB, Azzarelli R, Rulands S, Nestorowa S, Hindley C, Nichols J, Göttgens B, Huch M, Philpott A, Simons B. 2018. Defining lineage potential and fate behavior of precursors during pancreas development. Developmental Cell. 46(3), 360–375.","ieee":"M. Sznurkowska <i>et al.</i>, “Defining lineage potential and fate behavior of precursors during pancreas development,” <i>Developmental Cell</i>, vol. 46, no. 3. Cell Press, pp. 360–375, 2018.","apa":"Sznurkowska, M., Hannezo, E. B., Azzarelli, R., Rulands, S., Nestorowa, S., Hindley, C., … Simons, B. (2018). Defining lineage potential and fate behavior of precursors during pancreas development. <i>Developmental Cell</i>. Cell Press. <a href=\"https://doi.org/10.1016/j.devcel.2018.06.028\">https://doi.org/10.1016/j.devcel.2018.06.028</a>"},"file_date_updated":"2020-07-14T12:44:43Z","ddc":["570"],"month":"08","oa_version":"Published Version","file":[{"file_id":"5694","date_created":"2018-12-17T10:49:49Z","access_level":"open_access","content_type":"application/pdf","checksum":"78d2062b9e3c3b90fe71545aeb6d2f65","date_updated":"2020-07-14T12:44:43Z","file_name":"2018_DevelopmentalCell_Sznurkowska.pdf","file_size":8948384,"relation":"main_file","creator":"dernst"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"has_accepted_license":"1","article_processing_charge":"No","volume":46,"author":[{"full_name":"Sznurkowska, Magdalena","last_name":"Sznurkowska","first_name":"Magdalena"},{"id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","first_name":"Edouard B","full_name":"Hannezo, Edouard B","last_name":"Hannezo","orcid":"0000-0001-6005-1561"},{"first_name":"Roberta","last_name":"Azzarelli","full_name":"Azzarelli, Roberta"},{"full_name":"Rulands, Steffen","last_name":"Rulands","first_name":"Steffen"},{"first_name":"Sonia","last_name":"Nestorowa","full_name":"Nestorowa, Sonia"},{"first_name":"Christopher","last_name":"Hindley","full_name":"Hindley, Christopher"},{"last_name":"Nichols","full_name":"Nichols, Jennifer","first_name":"Jennifer"},{"first_name":"Berthold","full_name":"Göttgens, Berthold","last_name":"Göttgens"},{"first_name":"Meritxell","full_name":"Huch, Meritxell","last_name":"Huch"},{"full_name":"Philpott, Anna","last_name":"Philpott","first_name":"Anna"},{"last_name":"Simons","full_name":"Simons, Benjamin","first_name":"Benjamin"}],"title":"Defining lineage potential and fate behavior of precursors during pancreas development","_id":"132","issue":"3","abstract":[{"lang":"eng","text":"Pancreas development involves a coordinated process in which an early phase of cell segregation is followed by a longer phase of lineage restriction, expansion, and tissue remodeling. By combining clonal tracing and whole-mount reconstruction with proliferation kinetics and single-cell transcriptional profiling, we define the functional basis of pancreas morphogenesis. We show that the large-scale organization of mouse pancreas can be traced to the activity of self-renewing precursors positioned at the termini of growing ducts, which act collectively to drive serial rounds of stochastic ductal bifurcation balanced by termination. During this phase of branching morphogenesis, multipotent precursors become progressively fate-restricted, giving rise to self-renewing acinar-committed precursors that are conveyed with growing ducts, as well as ductal progenitors that expand the trailing ducts and give rise to delaminating endocrine cells. These findings define quantitatively how the functional behavior and lineage progression of precursor pools determine the large-scale patterning of pancreatic sub-compartments."}],"doi":"10.1016/j.devcel.2018.06.028","status":"public","publication_status":"published","acknowledgement":"E.H. is funded by a Junior Research Fellowship from Trinity College, Cam-bridge, a Sir Henry Wellcome Fellowship from the Wellcome Trust, and theBettencourt-Schueller Young Researcher Prize for support.","department":[{"_id":"EdHa"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publist_id":"7791","date_published":"2018-08-06T00:00:00Z","external_id":{"isi":["000441327300012"]},"scopus_import":"1","date_created":"2018-12-11T11:44:48Z","intvolume":"        46","publisher":"Cell Press","isi":1,"quality_controlled":"1","type":"journal_article","language":[{"iso":"eng"}],"oa":1,"year":"2018","publication":"Developmental Cell","date_updated":"2023-09-11T12:52:41Z","article_type":"original","page":"360 - 375"},{"language":[{"iso":"eng"}],"quality_controlled":"1","type":"conference","intvolume":"       118","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","scopus_import":1,"date_created":"2018-12-11T11:44:48Z","date_published":"2018-08-13T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publist_id":"7790","department":[{"_id":"ToHe"}],"article_number":"21","related_material":{"record":[{"status":"public","relation":"earlier_version","id":"6426"},{"status":"public","relation":"dissertation_contains","id":"8332"}]},"date_updated":"2023-09-07T13:18:00Z","year":"2018","alternative_title":["LIPIcs"],"oa":1,"volume":118,"has_accepted_license":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"access_level":"open_access","content_type":"application/pdf","checksum":"c90895f4c5fafc18ddc54d1c8848077e","date_updated":"2020-07-14T12:44:44Z","file_name":"IST-2018-853-v2+2_concur2018.pdf","file_size":745438,"creator":"system","relation":"main_file","file_id":"5368","date_created":"2018-12-12T10:18:46Z"}],"conference":{"name":"CONCUR: International Conference on Concurrency Theory","start_date":"2018-09-04","location":"Beijing, China","end_date":"2018-09-07"},"oa_version":"Published Version","ddc":["000"],"file_date_updated":"2020-07-14T12:44:44Z","month":"08","day":"13","pubrep_id":"1039","citation":{"mla":"Kragl, Bernhard, et al. <i>Synchronizing the Asynchronous</i>. Vol. 118, 21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018, doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2018.21\">10.4230/LIPIcs.CONCUR.2018.21</a>.","chicago":"Kragl, Bernhard, Shaz Qadeer, and Thomas A Henzinger. “Synchronizing the Asynchronous,” Vol. 118. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2018.21\">https://doi.org/10.4230/LIPIcs.CONCUR.2018.21</a>.","apa":"Kragl, B., Qadeer, S., &#38; Henzinger, T. A. (2018). Synchronizing the asynchronous (Vol. 118). Presented at the CONCUR: International Conference on Concurrency Theory, Beijing, China: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2018.21\">https://doi.org/10.4230/LIPIcs.CONCUR.2018.21</a>","ieee":"B. Kragl, S. Qadeer, and T. A. Henzinger, “Synchronizing the asynchronous,” presented at the CONCUR: International Conference on Concurrency Theory, Beijing, China, 2018, vol. 118.","ama":"Kragl B, Qadeer S, Henzinger TA. Synchronizing the asynchronous. In: Vol 118. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2018. doi:<a href=\"https://doi.org/10.4230/LIPIcs.CONCUR.2018.21\">10.4230/LIPIcs.CONCUR.2018.21</a>","ista":"Kragl B, Qadeer S, Henzinger TA. 2018. Synchronizing the asynchronous. CONCUR: International Conference on Concurrency Theory, LIPIcs, vol. 118, 21.","short":"B. Kragl, S. Qadeer, T.A. Henzinger, in:, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018."},"publication_status":"published","status":"public","project":[{"name":"Rigorous Systems Engineering","call_identifier":"FWF","grant_number":"S11402-N23","_id":"25F2ACDE-B435-11E9-9278-68D0E5697425"},{"name":"Moderne Concurrency Paradigms","call_identifier":"FWF","grant_number":"S11402-N23","_id":"25F5A88A-B435-11E9-9278-68D0E5697425"}],"publication_identifier":{"issn":["18688969"]},"doi":"10.4230/LIPIcs.CONCUR.2018.21","abstract":[{"lang":"eng","text":"Synchronous programs are easy to specify because the side effects of an operation are finished by the time the invocation of the operation returns to the caller. Asynchronous programs, on the other hand, are difficult to specify because there are side effects due to pending computation scheduled as a result of the invocation of an operation. They are also difficult to verify because of the large number of possible interleavings of concurrent computation threads. We present synchronization, a new proof rule that simplifies the verification of asynchronous programs by introducing the fiction, for proof purposes, that asynchronous operations complete synchronously. Synchronization summarizes an asynchronous computation as immediate atomic effect. Modular verification is enabled via pending asynchronous calls in atomic summaries, and a complementary proof rule that eliminates pending asynchronous calls when components and their specifications are composed. We evaluate synchronization in the context of a multi-layer refinement verification methodology on a collection of benchmark programs."}],"_id":"133","author":[{"last_name":"Kragl","full_name":"Kragl, Bernhard","first_name":"Bernhard","id":"320FC952-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7745-9117"},{"last_name":"Qadeer","full_name":"Qadeer, Shaz","first_name":"Shaz"},{"orcid":"0000−0002−2985−7724","full_name":"Henzinger, Thomas A","last_name":"Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A"}],"title":"Synchronizing the asynchronous"},{"department":[{"_id":"ChWo"}],"publist_id":"7789","user_id":"2EBD1598-F248-11E8-B48F-1D18A9856A87","external_id":{"isi":["000448185000055"]},"date_published":"2018-07-30T00:00:00Z","date_created":"2018-12-11T11:44:48Z","acknowledged_ssus":[{"_id":"ScienComp"}],"scopus_import":"1","publisher":"ACM","intvolume":"        37","isi":1,"type":"journal_article","quality_controlled":"1","language":[{"iso":"eng"}],"oa":1,"alternative_title":["SIGGRAPH"],"year":"2018","publication":"ACM Transactions on Graphics","date_updated":"2024-02-28T13:58:51Z","related_material":{"link":[{"url":"https://ist.ac.at/en/news/new-water-simulation-captures-small-details-even-in-large-scenes/","description":"News on IST Homepage","relation":"press_release"}]},"article_number":"94","citation":{"short":"S. Jeschke, T. Skrivan, M. Mueller Fischer, N. Chentanez, M. Macklin, C. Wojtan, ACM Transactions on Graphics 37 (2018).","ama":"Jeschke S, Skrivan T, Mueller Fischer M, Chentanez N, Macklin M, Wojtan C. Water surface wavelets. <i>ACM Transactions on Graphics</i>. 2018;37(4). doi:<a href=\"https://doi.org/10.1145/3197517.3201336\">10.1145/3197517.3201336</a>","ista":"Jeschke S, Skrivan T, Mueller Fischer M, Chentanez N, Macklin M, Wojtan C. 2018. Water surface wavelets. ACM Transactions on Graphics. 37(4), 94.","ieee":"S. Jeschke, T. Skrivan, M. Mueller Fischer, N. Chentanez, M. Macklin, and C. Wojtan, “Water surface wavelets,” <i>ACM Transactions on Graphics</i>, vol. 37, no. 4. ACM, 2018.","apa":"Jeschke, S., Skrivan, T., Mueller Fischer, M., Chentanez, N., Macklin, M., &#38; Wojtan, C. (2018). Water surface wavelets. <i>ACM Transactions on Graphics</i>. ACM. <a href=\"https://doi.org/10.1145/3197517.3201336\">https://doi.org/10.1145/3197517.3201336</a>","mla":"Jeschke, Stefan, et al. “Water Surface Wavelets.” <i>ACM Transactions on Graphics</i>, vol. 37, no. 4, 94, ACM, 2018, doi:<a href=\"https://doi.org/10.1145/3197517.3201336\">10.1145/3197517.3201336</a>.","chicago":"Jeschke, Stefan, Tomas Skrivan, Matthias Mueller Fischer, Nuttapong Chentanez, Miles Macklin, and Chris Wojtan. “Water Surface Wavelets.” <i>ACM Transactions on Graphics</i>. ACM, 2018. <a href=\"https://doi.org/10.1145/3197517.3201336\">https://doi.org/10.1145/3197517.3201336</a>."},"day":"30","ddc":["000"],"month":"07","file_date_updated":"2020-07-14T12:44:45Z","license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","oa_version":"Published Version","tmp":{"image":"/images/cc_by_nc_sa.png","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","short":"CC BY-NC-SA (4.0)"},"file":[{"file_name":"2018_ACM_Jeschke.pdf","creator":"dernst","relation":"main_file","file_size":22185016,"date_updated":"2020-07-14T12:44:45Z","access_level":"open_access","checksum":"db75ebabe2ec432bf41389e614d6ef62","content_type":"application/pdf","file_id":"5744","date_created":"2018-12-18T09:59:23Z"}],"has_accepted_license":"1","volume":37,"article_processing_charge":"No","title":"Water surface wavelets","author":[{"first_name":"Stefan","id":"44D6411A-F248-11E8-B48F-1D18A9856A87","last_name":"Jeschke","full_name":"Jeschke, Stefan"},{"last_name":"Skrivan","full_name":"Skrivan, Tomas","first_name":"Tomas","id":"486A5A46-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Mueller Fischer, Matthias","last_name":"Mueller Fischer","first_name":"Matthias"},{"first_name":"Nuttapong","full_name":"Chentanez, Nuttapong","last_name":"Chentanez"},{"first_name":"Miles","last_name":"Macklin","full_name":"Macklin, Miles"},{"orcid":"0000-0001-6646-5546","first_name":"Christopher J","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","last_name":"Wojtan","full_name":"Wojtan, Christopher J"}],"_id":"134","abstract":[{"lang":"eng","text":"The current state of the art in real-time two-dimensional water wave simulation requires developers to choose between efficient Fourier-based methods, which lack interactions with moving obstacles, and finite-difference or finite element methods, which handle environmental interactions but are significantly more expensive. This paper attempts to bridge this long-standing gap between complexity and performance, by proposing a new wave simulation method that can faithfully simulate wave interactions with moving obstacles in real time while simultaneously preserving minute details and accommodating very large simulation domains.\r\n\r\nPrevious methods for simulating 2D water waves directly compute the change in height of the water surface, a strategy which imposes limitations based on the CFL condition (fast moving waves require small time steps) and Nyquist's limit (small wave details require closely-spaced simulation variables). This paper proposes a novel wavelet transformation that discretizes the liquid motion in terms of amplitude-like functions that vary over space, frequency, and direction, effectively generalizing Fourier-based methods to handle local interactions. Because these new variables change much more slowly over space than the original water height function, our change of variables drastically reduces the limitations of the CFL condition and Nyquist limit, allowing us to simulate highly detailed water waves at very large visual resolutions. Our discretization is amenable to fast summation and easy to parallelize. We also present basic extensions like pre-computed wave paths and two-way solid fluid coupling. Finally, we argue that our discretization provides a convenient set of variables for artistic manipulation, which we illustrate with a novel wave-painting interface."}],"issue":"4","doi":"10.1145/3197517.3201336","project":[{"call_identifier":"H2020","name":"Efficient Simulation of Natural Phenomena at Extremely Large Scales","grant_number":"638176","_id":"2533E772-B435-11E9-9278-68D0E5697425"},{"name":"International IST Doctoral Program","call_identifier":"H2020","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385"}],"status":"public","publication_status":"published","ec_funded":1},{"scopus_import":"1","date_created":"2018-12-11T11:44:49Z","external_id":{"isi":["000434085600016"]},"date_published":"2018-05-22T00:00:00Z","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","department":[{"_id":"ChWo"}],"type":"journal_article","language":[{"iso":"eng"}],"quality_controlled":"1","isi":1,"intvolume":"        37","publisher":"Wiley","alternative_title":["Eurographics"],"year":"2018","oa":1,"article_type":"original","page":"169 - 177","date_updated":"2023-09-11T14:00:26Z","publication":"Computer Graphics Forum","oa_version":"Submitted Version","file_date_updated":"2020-10-08T08:38:23Z","month":"05","ddc":["006"],"day":"22","citation":{"apa":"Sato, T., Wojtan, C., Thuerey, N., Igarashi, T., &#38; Ando, R. (2018). Extended narrow band FLIP for liquid simulations. <i>Computer Graphics Forum</i>. Wiley. <a href=\"https://doi.org/10.1111/cgf.13351\">https://doi.org/10.1111/cgf.13351</a>","ieee":"T. Sato, C. Wojtan, N. Thuerey, T. Igarashi, and R. Ando, “Extended narrow band FLIP for liquid simulations,” <i>Computer Graphics Forum</i>, vol. 37, no. 2. Wiley, pp. 169–177, 2018.","short":"T. Sato, C. Wojtan, N. Thuerey, T. Igarashi, R. Ando, Computer Graphics Forum 37 (2018) 169–177.","ama":"Sato T, Wojtan C, Thuerey N, Igarashi T, Ando R. Extended narrow band FLIP for liquid simulations. <i>Computer Graphics Forum</i>. 2018;37(2):169-177. doi:<a href=\"https://doi.org/10.1111/cgf.13351\">10.1111/cgf.13351</a>","ista":"Sato T, Wojtan C, Thuerey N, Igarashi T, Ando R. 2018. Extended narrow band FLIP for liquid simulations. Computer Graphics Forum. 37(2), 169–177.","mla":"Sato, Takahiro, et al. “Extended Narrow Band FLIP for Liquid Simulations.” <i>Computer Graphics Forum</i>, vol. 37, no. 2, Wiley, 2018, pp. 169–77, doi:<a href=\"https://doi.org/10.1111/cgf.13351\">10.1111/cgf.13351</a>.","chicago":"Sato, Takahiro, Chris Wojtan, Nils Thuerey, Takeo Igarashi, and Ryoichi Ando. “Extended Narrow Band FLIP for Liquid Simulations.” <i>Computer Graphics Forum</i>. Wiley, 2018. <a href=\"https://doi.org/10.1111/cgf.13351\">https://doi.org/10.1111/cgf.13351</a>."},"article_processing_charge":"No","volume":37,"has_accepted_license":"1","file":[{"content_type":"application/pdf","checksum":"8edb90da8a72395eb5d970580e0925b6","access_level":"open_access","date_updated":"2020-10-08T08:38:23Z","success":1,"creator":"wojtan","relation":"main_file","file_size":54309947,"file_name":"exnbflip.pdf","date_created":"2020-10-08T08:38:23Z","file_id":"8627"}],"doi":"10.1111/cgf.13351","issue":"2","abstract":[{"lang":"eng","text":"The Fluid Implicit Particle method (FLIP) reduces numerical dissipation by combining particles with grids. To improve performance, the subsequent narrow band FLIP method (NB‐FLIP) uses a FLIP‐based fluid simulation only near the liquid surface and a traditional grid‐based fluid simulation away from the surface. This spatially‐limited FLIP simulation significantly reduces the number of particles and alleviates a computational bottleneck. In this paper, we extend the NB‐FLIP idea even further, by allowing a simulation to transition between a FLIP‐like fluid simulation and a grid‐based simulation in arbitrary locations, not just near the surface. This approach leads to even more savings in memory and computation, because we can concentrate the particles only in areas where they are needed. More importantly, this new method allows us to seamlessly transition to smooth implicit surface geometry wherever the particle‐based simulation is unnecessary. Consequently, our method leads to a practical algorithm for avoiding the noisy surface artifacts associated with particle‐based liquid simulations, while simultaneously maintaining the benefits of a FLIP simulation in regions of dynamic motion."}],"_id":"135","author":[{"first_name":"Takahiro","full_name":"Sato, Takahiro","last_name":"Sato"},{"orcid":"0000-0001-6646-5546","first_name":"Christopher J","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","last_name":"Wojtan","full_name":"Wojtan, Christopher J"},{"first_name":"Nils","last_name":"Thuerey","full_name":"Thuerey, Nils"},{"last_name":"Igarashi","full_name":"Igarashi, Takeo","first_name":"Takeo"},{"last_name":"Ando","full_name":"Ando, Ryoichi","first_name":"Ryoichi"}],"title":"Extended narrow band FLIP for liquid simulations","ec_funded":1,"status":"public","publication_status":"published","project":[{"_id":"2533E772-B435-11E9-9278-68D0E5697425","grant_number":"638176","name":"Efficient Simulation of Natural Phenomena at Extremely Large Scales","call_identifier":"H2020"}],"publication_identifier":{"issn":["0167-7055"]}},{"oa":1,"year":"2018","date_updated":"2023-10-10T13:29:10Z","publication":"Physical Review E","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"BjHo"}],"date_created":"2018-12-11T11:44:49Z","scopus_import":"1","date_published":"2018-08-13T00:00:00Z","external_id":{"isi":["000441466800010"],"arxiv":["1808.02088"]},"publisher":"American Physical Society","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1808.02088"}],"intvolume":"        98","type":"journal_article","language":[{"iso":"eng"}],"quality_controlled":"1","isi":1,"_id":"136","title":"Unstable equilibria and invariant manifolds in quasi-two-dimensional Kolmogorov-like flow","author":[{"last_name":"Suri","full_name":"Suri, Balachandra","first_name":"Balachandra","id":"47A5E706-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Jeffrey","full_name":"Tithof, Jeffrey","last_name":"Tithof"},{"first_name":"Roman","last_name":"Grigoriev","full_name":"Grigoriev, Roman"},{"full_name":"Schatz, Michael","last_name":"Schatz","first_name":"Michael"}],"doi":"10.1103/PhysRevE.98.023105","abstract":[{"lang":"eng","text":"Recent studies suggest that unstable, nonchaotic solutions of the Navier-Stokes equation may provide deep insights into fluid turbulence. In this article, we present a combined experimental and numerical study exploring the dynamical role of unstable equilibrium solutions and their invariant manifolds in a weakly turbulent, electromagnetically driven, shallow fluid layer. Identifying instants when turbulent evolution slows down, we compute 31 unstable equilibria of a realistic two-dimensional model of the flow. We establish the dynamical relevance of these unstable equilibria by showing that they are closely visited by the turbulent flow. We also establish the dynamical relevance of unstable manifolds by verifying that they are shadowed by turbulent trajectories departing from the neighborhoods of unstable equilibria over large distances in state space."}],"issue":"2","status":"public","publication_status":"published","month":"08","citation":{"apa":"Suri, B., Tithof, J., Grigoriev, R., &#38; Schatz, M. (2018). Unstable equilibria and invariant manifolds in quasi-two-dimensional Kolmogorov-like flow. <i>Physical Review E</i>. American Physical Society. <a href=\"https://doi.org/10.1103/PhysRevE.98.023105\">https://doi.org/10.1103/PhysRevE.98.023105</a>","ieee":"B. Suri, J. Tithof, R. Grigoriev, and M. Schatz, “Unstable equilibria and invariant manifolds in quasi-two-dimensional Kolmogorov-like flow,” <i>Physical Review E</i>, vol. 98, no. 2. American Physical Society, 2018.","ista":"Suri B, Tithof J, Grigoriev R, Schatz M. 2018. Unstable equilibria and invariant manifolds in quasi-two-dimensional Kolmogorov-like flow. Physical Review E. 98(2).","ama":"Suri B, Tithof J, Grigoriev R, Schatz M. Unstable equilibria and invariant manifolds in quasi-two-dimensional Kolmogorov-like flow. <i>Physical Review E</i>. 2018;98(2). doi:<a href=\"https://doi.org/10.1103/PhysRevE.98.023105\">10.1103/PhysRevE.98.023105</a>","short":"B. Suri, J. Tithof, R. Grigoriev, M. Schatz, Physical Review E 98 (2018).","chicago":"Suri, Balachandra, Jeffrey Tithof, Roman Grigoriev, and Michael Schatz. “Unstable Equilibria and Invariant Manifolds in Quasi-Two-Dimensional Kolmogorov-like Flow.” <i>Physical Review E</i>. American Physical Society, 2018. <a href=\"https://doi.org/10.1103/PhysRevE.98.023105\">https://doi.org/10.1103/PhysRevE.98.023105</a>.","mla":"Suri, Balachandra, et al. “Unstable Equilibria and Invariant Manifolds in Quasi-Two-Dimensional Kolmogorov-like Flow.” <i>Physical Review E</i>, vol. 98, no. 2, American Physical Society, 2018, doi:<a href=\"https://doi.org/10.1103/PhysRevE.98.023105\">10.1103/PhysRevE.98.023105</a>."},"day":"13","oa_version":"Submitted Version","arxiv":1,"article_processing_charge":"No","volume":98},{"status":"public","publication_status":"published","project":[{"grant_number":"RGY0084/2012","_id":"255BFFFA-B435-11E9-9278-68D0E5697425","name":"In situ real-time imaging of neurotransmitter signaling using designer optical sensors (HFSP Young Investigator)"}],"doi":"10.1038/s41589-018-0108-2","issue":"9","abstract":[{"text":"Fluorescent sensors are an essential part of the experimental toolbox of the life sciences, where they are used ubiquitously to visualize intra- and extracellular signaling. In the brain, optical neurotransmitter sensors can shed light on temporal and spatial aspects of signal transmission by directly observing, for instance, neurotransmitter release and spread. Here we report the development and application of the first optical sensor for the amino acid glycine, which is both an inhibitory neurotransmitter and a co-agonist of the N-methyl-d-aspartate receptors (NMDARs) involved in synaptic plasticity. Computational design of a glycine-specific binding protein allowed us to produce the optical glycine FRET sensor (GlyFS), which can be used with single and two-photon excitation fluorescence microscopy. We took advantage of this newly developed sensor to test predictions about the uneven spatial distribution of glycine in extracellular space and to demonstrate that extracellular glycine levels are controlled by plasticity-inducing stimuli.","lang":"eng"}],"_id":"137","author":[{"first_name":"William","last_name":"Zhang","full_name":"Zhang, William"},{"first_name":"Michel","full_name":"Herde, Michel","last_name":"Herde"},{"last_name":"Mitchell","full_name":"Mitchell, Joshua","first_name":"Joshua"},{"last_name":"Whitfield","full_name":"Whitfield, Jason","first_name":"Jason"},{"first_name":"Andreas","full_name":"Wulff, Andreas","last_name":"Wulff"},{"first_name":"Vanessa","full_name":"Vongsouthi, Vanessa","last_name":"Vongsouthi"},{"id":"3D9C5D30-F248-11E8-B48F-1D18A9856A87","first_name":"Inmaculada","full_name":"Sanchez Romero, Inmaculada","last_name":"Sanchez Romero"},{"first_name":"Polina","last_name":"Gulakova","full_name":"Gulakova, Polina"},{"last_name":"Minge","full_name":"Minge, Daniel","first_name":"Daniel"},{"last_name":"Breithausen","full_name":"Breithausen, Björn","first_name":"Björn"},{"full_name":"Schoch, Susanne","last_name":"Schoch","first_name":"Susanne"},{"orcid":"0000-0002-8023-9315","full_name":"Janovjak, Harald L","last_name":"Janovjak","id":"33BA6C30-F248-11E8-B48F-1D18A9856A87","first_name":"Harald L"},{"last_name":"Jackson","full_name":"Jackson, Colin","first_name":"Colin"},{"last_name":"Henneberger","full_name":"Henneberger, Christian","first_name":"Christian"}],"title":"Monitoring hippocampal glycine with the computationally designed optical sensor GlyFS","article_processing_charge":"No","volume":14,"oa_version":"Submitted Version","pmid":1,"month":"07","day":"30","citation":{"apa":"Zhang, W., Herde, M., Mitchell, J., Whitfield, J., Wulff, A., Vongsouthi, V., … Henneberger, C. (2018). Monitoring hippocampal glycine with the computationally designed optical sensor GlyFS. <i>Nature Chemical Biology</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/s41589-018-0108-2\">https://doi.org/10.1038/s41589-018-0108-2</a>","ieee":"W. Zhang <i>et al.</i>, “Monitoring hippocampal glycine with the computationally designed optical sensor GlyFS,” <i>Nature Chemical Biology</i>, vol. 14, no. 9. Nature Publishing Group, pp. 861–869, 2018.","short":"W. Zhang, M. Herde, J. Mitchell, J. Whitfield, A. Wulff, V. Vongsouthi, I. Sanchez-Romero, P. Gulakova, D. Minge, B. Breithausen, S. Schoch, H.L. Janovjak, C. Jackson, C. Henneberger, Nature Chemical Biology 14 (2018) 861–869.","ama":"Zhang W, Herde M, Mitchell J, et al. Monitoring hippocampal glycine with the computationally designed optical sensor GlyFS. <i>Nature Chemical Biology</i>. 2018;14(9):861-869. doi:<a href=\"https://doi.org/10.1038/s41589-018-0108-2\">10.1038/s41589-018-0108-2</a>","ista":"Zhang W, Herde M, Mitchell J, Whitfield J, Wulff A, Vongsouthi V, Sanchez-Romero I, Gulakova P, Minge D, Breithausen B, Schoch S, Janovjak HL, Jackson C, Henneberger C. 2018. Monitoring hippocampal glycine with the computationally designed optical sensor GlyFS. Nature Chemical Biology. 14(9), 861–869.","mla":"Zhang, William, et al. “Monitoring Hippocampal Glycine with the Computationally Designed Optical Sensor GlyFS.” <i>Nature Chemical Biology</i>, vol. 14, no. 9, Nature Publishing Group, 2018, pp. 861–69, doi:<a href=\"https://doi.org/10.1038/s41589-018-0108-2\">10.1038/s41589-018-0108-2</a>.","chicago":"Zhang, William, Michel Herde, Joshua Mitchell, Jason Whitfield, Andreas Wulff, Vanessa Vongsouthi, Inmaculada Sanchez-Romero, et al. “Monitoring Hippocampal Glycine with the Computationally Designed Optical Sensor GlyFS.” <i>Nature Chemical Biology</i>. Nature Publishing Group, 2018. <a href=\"https://doi.org/10.1038/s41589-018-0108-2\">https://doi.org/10.1038/s41589-018-0108-2</a>."},"article_type":"original","page":"861 - 869","date_updated":"2023-09-13T08:58:05Z","publication":"Nature Chemical Biology","year":"2018","oa":1,"quality_controlled":"1","language":[{"iso":"eng"}],"type":"journal_article","isi":1,"intvolume":"        14","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pubmed/30061718","open_access":"1"}],"publisher":"Nature Publishing Group","scopus_import":"1","date_created":"2018-12-11T11:44:49Z","date_published":"2018-07-30T00:00:00Z","external_id":{"isi":["000442174500013"],"pmid":["30061718 "]},"publist_id":"7786","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","department":[{"_id":"HaJa"}]},{"oa_version":"Published Version","citation":{"ieee":"C. Fraisse <i>et al.</i>, “The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies,” <i>PeerJ</i>, vol. 2018, no. 7. PeerJ, 2018.","apa":"Fraisse, C., Roux, C., Gagnaire, P., Romiguier, J., Faivre, N., Welch, J., &#38; Bierne, N. (2018). The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies. <i>PeerJ</i>. PeerJ. <a href=\"https://doi.org/10.7717/peerj.5198\">https://doi.org/10.7717/peerj.5198</a>","ama":"Fraisse C, Roux C, Gagnaire P, et al. The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies. <i>PeerJ</i>. 2018;2018(7). doi:<a href=\"https://doi.org/10.7717/peerj.5198\">10.7717/peerj.5198</a>","ista":"Fraisse C, Roux C, Gagnaire P, Romiguier J, Faivre N, Welch J, Bierne N. 2018. The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies. PeerJ. 2018(7), 30083438.","short":"C. Fraisse, C. Roux, P. Gagnaire, J. Romiguier, N. Faivre, J. Welch, N. Bierne, PeerJ 2018 (2018).","mla":"Fraisse, Christelle, et al. “The Divergence History of European Blue Mussel Species Reconstructed from Approximate Bayesian Computation: The Effects of Sequencing Techniques and Sampling Strategies.” <i>PeerJ</i>, vol. 2018, no. 7, 30083438, PeerJ, 2018, doi:<a href=\"https://doi.org/10.7717/peerj.5198\">10.7717/peerj.5198</a>.","chicago":"Fraisse, Christelle, Camille Roux, Pierre Gagnaire, Jonathan Romiguier, Nicolas Faivre, John Welch, and Nicolas Bierne. “The Divergence History of European Blue Mussel Species Reconstructed from Approximate Bayesian Computation: The Effects of Sequencing Techniques and Sampling Strategies.” <i>PeerJ</i>. PeerJ, 2018. <a href=\"https://doi.org/10.7717/peerj.5198\">https://doi.org/10.7717/peerj.5198</a>."},"day":"30","file_date_updated":"2020-07-14T12:44:48Z","ddc":["576"],"month":"07","has_accepted_license":"1","volume":2018,"article_processing_charge":"No","file":[{"file_id":"5739","date_created":"2018-12-18T09:42:11Z","date_updated":"2020-07-14T12:44:48Z","access_level":"open_access","checksum":"7d55ae22598a1c70759cd671600cff53","content_type":"application/pdf","file_name":"2018_PeerJ_Fraisse.pdf","relation":"main_file","creator":"dernst","file_size":1480792}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"abstract":[{"lang":"eng","text":"Genome-scale diversity data are increasingly available in a variety of biological systems, and can be used to reconstruct the past evolutionary history of species divergence. However, extracting the full demographic information from these data is not trivial, and requires inferential methods that account for the diversity of coalescent histories throughout the genome. Here, we evaluate the potential and limitations of one such approach. We reexamine a well-known system of mussel sister species, using the joint site frequency spectrum (jSFS) of synonymousmutations computed either fromexome capture or RNA-seq, in an Approximate Bayesian Computation (ABC) framework. We first assess the best sampling strategy (number of: individuals, loci, and bins in the jSFS), and show that model selection is robust to variation in the number of individuals and loci. In contrast, different binning choices when summarizing the jSFS, strongly affect the results: including classes of low and high frequency shared polymorphisms can more effectively reveal recent migration events. We then take advantage of the flexibility of ABC to compare more realistic models of speciation, including variation in migration rates through time (i.e., periodic connectivity) and across genes (i.e., genome-wide heterogeneity in migration rates). We show that these models were consistently selected as the most probable, suggesting that mussels have experienced a complex history of gene flow during divergence and that the species boundary is semi-permeable. Our work provides a comprehensive evaluation of ABC demographic inference in mussels based on the coding jSFS, and supplies guidelines for employing different sequencing techniques and sampling strategies. We emphasize, perhaps surprisingly, that inferences are less limited by the volume of data, than by the way in which they are analyzed."}],"issue":"7","doi":"10.7717/peerj.5198","title":"The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies","author":[{"orcid":"0000-0001-8441-5075","full_name":"Fraisse, Christelle","last_name":"Fraisse","id":"32DF5794-F248-11E8-B48F-1D18A9856A87","first_name":"Christelle"},{"first_name":"Camille","full_name":"Roux, Camille","last_name":"Roux"},{"first_name":"Pierre","last_name":"Gagnaire","full_name":"Gagnaire, Pierre"},{"full_name":"Romiguier, Jonathan","last_name":"Romiguier","first_name":"Jonathan"},{"last_name":"Faivre","full_name":"Faivre, Nicolas","first_name":"Nicolas"},{"first_name":"John","last_name":"Welch","full_name":"Welch, John"},{"last_name":"Bierne","full_name":"Bierne, Nicolas","first_name":"Nicolas"}],"_id":"139","publication_status":"published","status":"public","external_id":{"isi":["000440484800002"]},"date_published":"2018-07-30T00:00:00Z","date_created":"2018-12-11T11:44:50Z","scopus_import":"1","department":[{"_id":"BeVi"},{"_id":"NiBa"}],"publist_id":"7784","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","isi":1,"type":"journal_article","language":[{"iso":"eng"}],"quality_controlled":"1","publisher":"PeerJ","intvolume":"      2018","year":"2018","oa":1,"article_number":"30083438","publication":"PeerJ","date_updated":"2023-10-17T12:25:28Z"},{"oa_version":"Published Version","day":"12","citation":{"short":"S. Hille, M. Akhmanova, M. Glanc, A.J. Johnson, J. Friml, International Journal of Molecular Sciences 19 (2018).","ista":"Hille S, Akhmanova M, Glanc M, Johnson AJ, Friml J. 2018. Relative contribution of PIN-containing secretory vesicles and plasma membrane PINs to the directed auxin transport: Theoretical estimation. International Journal of Molecular Sciences. 19(11).","ama":"Hille S, Akhmanova M, Glanc M, Johnson AJ, Friml J. Relative contribution of PIN-containing secretory vesicles and plasma membrane PINs to the directed auxin transport: Theoretical estimation. <i>International Journal of Molecular Sciences</i>. 2018;19(11). doi:<a href=\"https://doi.org/10.3390/ijms19113566\">10.3390/ijms19113566</a>","apa":"Hille, S., Akhmanova, M., Glanc, M., Johnson, A. J., &#38; Friml, J. (2018). Relative contribution of PIN-containing secretory vesicles and plasma membrane PINs to the directed auxin transport: Theoretical estimation. <i>International Journal of Molecular Sciences</i>. MDPI. <a href=\"https://doi.org/10.3390/ijms19113566\">https://doi.org/10.3390/ijms19113566</a>","ieee":"S. Hille, M. Akhmanova, M. Glanc, A. J. Johnson, and J. Friml, “Relative contribution of PIN-containing secretory vesicles and plasma membrane PINs to the directed auxin transport: Theoretical estimation,” <i>International Journal of Molecular Sciences</i>, vol. 19, no. 11. MDPI, 2018.","chicago":"Hille, Sander, Maria Akhmanova, Matous Glanc, Alexander J Johnson, and Jiří Friml. “Relative Contribution of PIN-Containing Secretory Vesicles and Plasma Membrane PINs to the Directed Auxin Transport: Theoretical Estimation.” <i>International Journal of Molecular Sciences</i>. MDPI, 2018. <a href=\"https://doi.org/10.3390/ijms19113566\">https://doi.org/10.3390/ijms19113566</a>.","mla":"Hille, Sander, et al. “Relative Contribution of PIN-Containing Secretory Vesicles and Plasma Membrane PINs to the Directed Auxin Transport: Theoretical Estimation.” <i>International Journal of Molecular Sciences</i>, vol. 19, no. 11, MDPI, 2018, doi:<a href=\"https://doi.org/10.3390/ijms19113566\">10.3390/ijms19113566</a>."},"file_date_updated":"2020-07-14T12:44:50Z","ddc":["580"],"month":"11","has_accepted_license":"1","volume":19,"article_processing_charge":"No","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"file":[{"access_level":"open_access","checksum":"e4b59c2599b0ca26ebf5b8434bcde94a","content_type":"application/pdf","date_updated":"2020-07-14T12:44:50Z","file_name":"2018_IJMS_Hille.pdf","creator":"dernst","file_size":2200593,"relation":"main_file","file_id":"5719","date_created":"2018-12-17T16:04:11Z"}],"issue":"11","abstract":[{"lang":"eng","text":"The intercellular transport of auxin is driven by PIN-formed (PIN) auxin efflux carriers. PINs are localized at the plasma membrane (PM) and on constitutively recycling endomembrane vesicles. Therefore, PINs can mediate auxin transport either by direct translocation across the PM or by pumping auxin into secretory vesicles (SVs), leading to its secretory release upon fusion with the PM. Which of these two mechanisms dominates is a matter of debate. Here, we addressed the issue with a mathematical modeling approach. We demonstrate that the efficiency of secretory transport depends on SV size, half-life of PINs on the PM, pH, exocytosis frequency and PIN density. 3D structured illumination microscopy (SIM) was used to determine PIN density on the PM. Combining this data with published values of the other parameters, we show that the transport activity of PINs in SVs would have to be at least 1000× greater than on the PM in order to produce a comparable macroscopic auxin transport. If both transport mechanisms operated simultaneously and PINs were equally active on SVs and PM, the contribution of secretion to the total auxin flux would be negligible. In conclusion, while secretory vesicle-mediated transport of auxin is an intriguing and theoretically possible model, it is unlikely to be a major mechanism of auxin transport inplanta."}],"doi":"10.3390/ijms19113566","author":[{"full_name":"Hille, Sander","last_name":"Hille","first_name":"Sander"},{"last_name":"Akhmanova","full_name":"Akhmanova, Maria","first_name":"Maria","id":"3425EC26-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1522-3162"},{"id":"1AE1EA24-02D0-11E9-9BAA-DAF4881429F2","first_name":"Matous","full_name":"Glanc, Matous","last_name":"Glanc","orcid":"0000-0003-0619-7783"},{"first_name":"Alexander J","id":"46A62C3A-F248-11E8-B48F-1D18A9856A87","last_name":"Johnson","full_name":"Johnson, Alexander J","orcid":"0000-0002-2739-8843"},{"orcid":"0000-0002-8302-7596","full_name":"Friml, Jirí","last_name":"Friml","id":"4159519E-F248-11E8-B48F-1D18A9856A87","first_name":"Jirí"}],"title":"Relative contribution of PIN-containing secretory vesicles and plasma membrane PINs to the directed auxin transport: Theoretical estimation","_id":"14","status":"public","publication_status":"published","acknowledgement":"European Research Council (ERC): 742985 to Jiri Friml; M.A. was supported by the Austrian Science Fund (FWF) (M2379-B28); AJ was supported by the Austria Science Fund (FWF): I03630 to Jiri Friml.","ec_funded":1,"publication_identifier":{"eissn":["1422-0067"]},"project":[{"name":"Tracing Evolution of Auxin Transport and Polarity in Plants","call_identifier":"H2020","_id":"261099A6-B435-11E9-9278-68D0E5697425","grant_number":"742985"},{"name":"Molecular mechanisms of endocytic cargo recognition in plants","call_identifier":"FWF","_id":"26538374-B435-11E9-9278-68D0E5697425","grant_number":"I03630"}],"external_id":{"isi":["000451528500282"]},"date_published":"2018-11-12T00:00:00Z","scopus_import":"1","date_created":"2018-12-11T11:44:09Z","department":[{"_id":"DaSi"},{"_id":"JiFr"}],"publist_id":"8042","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","isi":1,"type":"journal_article","language":[{"iso":"eng"}],"quality_controlled":"1","intvolume":"        19","publisher":"MDPI","year":"2018","oa":1,"article_type":"original","publication":"International Journal of Molecular Sciences","date_updated":"2023-09-18T08:09:32Z"},{"publication_identifier":{"issn":["03029743"]},"project":[{"_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23","call_identifier":"FWF","name":"Rigorous Systems Engineering"},{"name":"Moderne Concurrency Paradigms","call_identifier":"FWF","grant_number":"S11402-N23","_id":"25F5A88A-B435-11E9-9278-68D0E5697425"}],"status":"public","publication_status":"published","title":"Space-time interpolants","author":[{"first_name":"Goran","last_name":"Frehse","full_name":"Frehse, Goran"},{"last_name":"Giacobbe","full_name":"Giacobbe, Mirco","first_name":"Mirco","id":"3444EA5E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8180-0904"},{"full_name":"Henzinger, Thomas A","last_name":"Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","orcid":"0000−0002−2985−7724"}],"_id":"140","abstract":[{"lang":"eng","text":"Reachability analysis is difficult for hybrid automata with affine differential equations, because the reach set needs to be approximated. Promising abstraction techniques usually employ interval methods or template polyhedra. Interval methods account for dense time and guarantee soundness, and there are interval-based tools that overapproximate affine flowpipes. But interval methods impose bounded and rigid shapes, which make refinement expensive and fixpoint detection difficult. Template polyhedra, on the other hand, can be adapted flexibly and can be unbounded, but sound template refinement for unbounded reachability analysis has been implemented only for systems with piecewise constant dynamics. We capitalize on the advantages of both techniques, combining interval arithmetic and template polyhedra, using the former to abstract time and the latter to abstract space. During a CEGAR loop, whenever a spurious error trajectory is found, we compute additional space constraints and split time intervals, and use these space-time interpolants to eliminate the counterexample. Space-time interpolation offers a lazy, flexible framework for increasing precision while guaranteeing soundness, both for error avoidance and fixpoint detection. To the best of out knowledge, this is the first abstraction refinement scheme for the reachability analysis over unbounded and dense time of affine hybrid systems, which is both sound and automatic. We demonstrate the effectiveness of our algorithm with several benchmark examples, which cannot be handled by other tools."}],"doi":"10.1007/978-3-319-96145-3_25","file":[{"access_level":"open_access","checksum":"6dca832f575d6b3f0ea9dff56f579142","content_type":"application/pdf","date_updated":"2020-07-14T12:44:50Z","file_name":"IST-2018-1010-v1+1_space-time_interpolants.pdf","creator":"system","relation":"main_file","file_size":563710,"file_id":"5310","date_created":"2018-12-12T10:17:53Z"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"has_accepted_license":"1","volume":10981,"article_processing_charge":"No","pubrep_id":"1010","citation":{"mla":"Frehse, Goran, et al. <i>Space-Time Interpolants</i>. Vol. 10981, Springer, 2018, pp. 468–86, doi:<a href=\"https://doi.org/10.1007/978-3-319-96145-3_25\">10.1007/978-3-319-96145-3_25</a>.","chicago":"Frehse, Goran, Mirco Giacobbe, and Thomas A Henzinger. “Space-Time Interpolants,” 10981:468–86. Springer, 2018. <a href=\"https://doi.org/10.1007/978-3-319-96145-3_25\">https://doi.org/10.1007/978-3-319-96145-3_25</a>.","apa":"Frehse, G., Giacobbe, M., &#38; Henzinger, T. A. (2018). Space-time interpolants (Vol. 10981, pp. 468–486). Presented at the CAV: Computer Aided Verification, Oxford, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-319-96145-3_25\">https://doi.org/10.1007/978-3-319-96145-3_25</a>","ieee":"G. Frehse, M. Giacobbe, and T. A. Henzinger, “Space-time interpolants,” presented at the CAV: Computer Aided Verification, Oxford, United Kingdom, 2018, vol. 10981, pp. 468–486.","short":"G. Frehse, M. Giacobbe, T.A. Henzinger, in:, Springer, 2018, pp. 468–486.","ama":"Frehse G, Giacobbe M, Henzinger TA. Space-time interpolants. In: Vol 10981. Springer; 2018:468-486. doi:<a href=\"https://doi.org/10.1007/978-3-319-96145-3_25\">10.1007/978-3-319-96145-3_25</a>","ista":"Frehse G, Giacobbe M, Henzinger TA. 2018. Space-time interpolants. CAV: Computer Aided Verification, LNCS, vol. 10981, 468–486."},"day":"18","month":"07","ddc":["005"],"file_date_updated":"2020-07-14T12:44:50Z","oa_version":"Published Version","conference":{"name":"CAV: Computer Aided Verification","location":"Oxford, United Kingdom","start_date":"2018-07-14","end_date":"2018-07-17"},"date_updated":"2023-09-19T09:30:43Z","related_material":{"record":[{"id":"6894","relation":"dissertation_contains","status":"public"}]},"page":"468 - 486","oa":1,"alternative_title":["LNCS"],"year":"2018","publisher":"Springer","intvolume":"     10981","isi":1,"type":"conference","language":[{"iso":"eng"}],"quality_controlled":"1","department":[{"_id":"ToHe"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publist_id":"7783","external_id":{"isi":["000491481600025"]},"date_published":"2018-07-18T00:00:00Z","date_created":"2018-12-11T11:44:50Z","scopus_import":"1"},{"page":"178-197","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"10199"}]},"date_updated":"2025-07-14T09:10:15Z","year":"2018","alternative_title":["LNCS"],"oa":1,"type":"conference","quality_controlled":"1","language":[{"iso":"eng"}],"isi":1,"intvolume":"     10982","publisher":"Springer","scopus_import":"1","date_created":"2018-12-11T11:44:51Z","external_id":{"isi":["000491469700013"]},"date_published":"2018-07-18T00:00:00Z","publist_id":"7782","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","department":[{"_id":"KrCh"}],"ec_funded":1,"publication_status":"published","acknowledgement":"Acknowledgements. K. C. and M. H. are partially supported by the Vienna Science and Technology Fund (WWTF) grant ICT15-003. K. C. is partially supported by the Austrian Science Fund (FWF): S11407-N23 (RiSE/SHiNE), and an ERC Start Grant (279307: Graph Games). V. T. is partially supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie Grant Agreement No. 665385.","status":"public","project":[{"name":"Quantitative Graph Games: Theory and Applications","call_identifier":"FP7","_id":"2581B60A-B435-11E9-9278-68D0E5697425","grant_number":"279307"},{"grant_number":"ICT15-003","_id":"25892FC0-B435-11E9-9278-68D0E5697425","name":"Efficient Algorithms for Computer Aided Verification"},{"grant_number":"S 11407_N23","_id":"25832EC2-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Rigorous Systems Engineering"},{"grant_number":"665385","_id":"2564DBCA-B435-11E9-9278-68D0E5697425","name":"International IST Doctoral Program","call_identifier":"H2020"}],"doi":"10.1007/978-3-319-96142-2_13","abstract":[{"lang":"eng","text":"Given a model and a specification, the fundamental model-checking problem asks for algorithmic verification of whether the model satisfies the specification. We consider graphs and Markov decision processes (MDPs), which are fundamental models for reactive systems. One of the very basic specifications that arise in verification of reactive systems is the strong fairness (aka Streett) objective. Given different types of requests and corresponding grants, the objective requires that for each type, if the request event happens infinitely often, then the corresponding grant event must also happen infinitely often. All ω -regular objectives can be expressed as Streett objectives and hence they are canonical in verification. To handle the state-space explosion, symbolic algorithms are required that operate on a succinct implicit representation of the system rather than explicitly accessing the system. While explicit algorithms for graphs and MDPs with Streett objectives have been widely studied, there has been no improvement of the basic symbolic algorithms. The worst-case numbers of symbolic steps required for the basic symbolic algorithms are as follows: quadratic for graphs and cubic for MDPs. In this work we present the first sub-quadratic symbolic algorithm for graphs with Streett objectives, and our algorithm is sub-quadratic even for MDPs. Based on our algorithmic insights we present an implementation of the new symbolic approach and show that it improves the existing approach on several academic benchmark examples."}],"_id":"141","author":[{"full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu","orcid":"0000-0002-4561-241X"},{"orcid":"0000-0002-5008-6530","id":"540c9bbd-f2de-11ec-812d-d04a5be85630","first_name":"Monika H","full_name":"Henzinger, Monika H","last_name":"Henzinger"},{"first_name":"Veronika","last_name":"Loitzenbauer","full_name":"Loitzenbauer, Veronika"},{"first_name":"Simin","last_name":"Oraee","full_name":"Oraee, Simin"},{"id":"3AF3DA7C-F248-11E8-B48F-1D18A9856A87","first_name":"Viktor","full_name":"Toman, Viktor","last_name":"Toman","orcid":"0000-0001-9036-063X"}],"title":"Symbolic algorithms for graphs and Markov decision processes with fairness objectives","article_processing_charge":"No","volume":10982,"has_accepted_license":"1","file":[{"file_name":"2018_LNCS_Chatterjee.pdf","file_size":675606,"relation":"main_file","creator":"dernst","access_level":"open_access","checksum":"1a6ffa4febe8bb8ac28be3adb3eafebc","content_type":"application/pdf","date_updated":"2020-07-14T12:44:53Z","file_id":"5737","date_created":"2018-12-18T08:52:38Z"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"conference":{"name":"CAV: Computer Aided Verification","start_date":"2018-07-14","location":"Oxford, United Kingdom","end_date":"2018-07-17"},"oa_version":"Published Version","file_date_updated":"2020-07-14T12:44:53Z","ddc":["000"],"month":"07","day":"18","citation":{"ista":"Chatterjee K, Henzinger MH, Loitzenbauer V, Oraee S, Toman V. 2018. Symbolic algorithms for graphs and Markov decision processes with fairness objectives. CAV: Computer Aided Verification, LNCS, vol. 10982, 178–197.","short":"K. Chatterjee, M.H. Henzinger, V. Loitzenbauer, S. Oraee, V. Toman, in:, Springer, 2018, pp. 178–197.","ama":"Chatterjee K, Henzinger MH, Loitzenbauer V, Oraee S, Toman V. Symbolic algorithms for graphs and Markov decision processes with fairness objectives. In: Vol 10982. Springer; 2018:178-197. doi:<a href=\"https://doi.org/10.1007/978-3-319-96142-2_13\">10.1007/978-3-319-96142-2_13</a>","ieee":"K. Chatterjee, M. H. Henzinger, V. Loitzenbauer, S. Oraee, and V. Toman, “Symbolic algorithms for graphs and Markov decision processes with fairness objectives,” presented at the CAV: Computer Aided Verification, Oxford, United Kingdom, 2018, vol. 10982, pp. 178–197.","apa":"Chatterjee, K., Henzinger, M. H., Loitzenbauer, V., Oraee, S., &#38; Toman, V. (2018). Symbolic algorithms for graphs and Markov decision processes with fairness objectives (Vol. 10982, pp. 178–197). Presented at the CAV: Computer Aided Verification, Oxford, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-319-96142-2_13\">https://doi.org/10.1007/978-3-319-96142-2_13</a>","mla":"Chatterjee, Krishnendu, et al. <i>Symbolic Algorithms for Graphs and Markov Decision Processes with Fairness Objectives</i>. Vol. 10982, Springer, 2018, pp. 178–97, doi:<a href=\"https://doi.org/10.1007/978-3-319-96142-2_13\">10.1007/978-3-319-96142-2_13</a>.","chicago":"Chatterjee, Krishnendu, Monika H Henzinger, Veronika Loitzenbauer, Simin Oraee, and Viktor Toman. “Symbolic Algorithms for Graphs and Markov Decision Processes with Fairness Objectives,” 10982:178–97. Springer, 2018. <a href=\"https://doi.org/10.1007/978-3-319-96142-2_13\">https://doi.org/10.1007/978-3-319-96142-2_13</a>."}},{"year":"2018","abstract":[{"text":"High-dimensional time series are common in many domains. Since human\r\ncognition is not optimized to work well in high-dimensional spaces, these areas\r\ncould benefit from interpretable low-dimensional representations. However, most\r\nrepresentation learning algorithms for time series data are difficult to\r\ninterpret. This is due to non-intuitive mappings from data features to salient\r\nproperties of the representation and non-smoothness over time. To address this\r\nproblem, we propose a new representation learning framework building on ideas\r\nfrom interpretable discrete dimensionality reduction and deep generative\r\nmodeling. This framework allows us to learn discrete representations of time\r\nseries, which give rise to smooth and interpretable embeddings with superior\r\nclustering performance. We introduce a new way to overcome the\r\nnon-differentiability in discrete representation learning and present a\r\ngradient-based version of the traditional self-organizing map algorithm that is\r\nmore performant than the original. Furthermore, to allow for a probabilistic\r\ninterpretation of our method, we integrate a Markov model in the representation\r\nspace. This model uncovers the temporal transition structure, improves\r\nclustering performance even further and provides additional explanatory\r\ninsights as well as a natural representation of uncertainty. We evaluate our\r\nmodel in terms of clustering performance and interpretability on static\r\n(Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST\r\nimages, a chaotic Lorenz attractor system with two macro states, as well as on\r\na challenging real world medical time series application on the eICU data set.\r\nOur learned representations compare favorably with competitor methods and\r\nfacilitate downstream tasks on the real world data.","lang":"eng"}],"author":[{"first_name":"Vincent","full_name":"Fortuin, Vincent","last_name":"Fortuin"},{"full_name":"Hüser, Matthias","last_name":"Hüser","first_name":"Matthias"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","full_name":"Locatello, Francesco","last_name":"Locatello","orcid":"0000-0002-4850-0683"},{"first_name":"Heiko","full_name":"Strathmann, Heiko","last_name":"Strathmann"},{"first_name":"Gunnar","last_name":"Rätsch","full_name":"Rätsch, Gunnar"}],"title":"SOM-VAE: Interpretable discrete representation learning on time series","oa":1,"_id":"14198","publication_status":"published","status":"public","publication":"International Conference on Learning Representations","date_updated":"2023-09-13T06:35:12Z","external_id":{"arxiv":["1806.02199"]},"date_published":"2018-06-06T00:00:00Z","extern":"1","conference":{"start_date":"2019-05-06","location":"New Orleans, LA, United States","end_date":"2019-05-09","name":"ICLR: International Conference on Learning Representations"},"date_created":"2023-08-22T14:12:48Z","oa_version":"Preprint","day":"06","department":[{"_id":"FrLo"}],"citation":{"chicago":"Fortuin, Vincent, Matthias Hüser, Francesco Locatello, Heiko Strathmann, and Gunnar Rätsch. “SOM-VAE: Interpretable Discrete Representation Learning on Time Series.” In <i>International Conference on Learning Representations</i>, 2018.","mla":"Fortuin, Vincent, et al. “SOM-VAE: Interpretable Discrete Representation Learning on Time Series.” <i>International Conference on Learning Representations</i>, 2018.","apa":"Fortuin, V., Hüser, M., Locatello, F., Strathmann, H., &#38; Rätsch, G. (2018). SOM-VAE: Interpretable discrete representation learning on time series. In <i>International Conference on Learning Representations</i>. New Orleans, LA, United States.","ieee":"V. Fortuin, M. Hüser, F. Locatello, H. Strathmann, and G. Rätsch, “SOM-VAE: Interpretable discrete representation learning on time series,” in <i>International Conference on Learning Representations</i>, New Orleans, LA, United States, 2018.","short":"V. Fortuin, M. Hüser, F. Locatello, H. Strathmann, G. Rätsch, in:, International Conference on Learning Representations, 2018.","ama":"Fortuin V, Hüser M, Locatello F, Strathmann H, Rätsch G. SOM-VAE: Interpretable discrete representation learning on time series. In: <i>International Conference on Learning Representations</i>. ; 2018.","ista":"Fortuin V, Hüser M, Locatello F, Strathmann H, Rätsch G. 2018. SOM-VAE: Interpretable discrete representation learning on time series. International Conference on Learning Representations. ICLR: International Conference on Learning Representations."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"06","type":"conference","language":[{"iso":"eng"}],"quality_controlled":"1","article_processing_charge":"No","arxiv":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1806.02199"}]},{"doi":"10.1007/978-3-319-96145-3_24","abstract":[{"lang":"eng","text":"We address the problem of analyzing the reachable set of a polynomial nonlinear continuous system by over-approximating the flowpipe of its dynamics. The common approach to tackle this problem is to perform a numerical integration over a given time horizon based on Taylor expansion and interval arithmetic. However, this method results to be very conservative when there is a large difference in speed between trajectories as time progresses. In this paper, we propose to use combinations of barrier functions, which we call piecewise barrier tube (PBT), to over-approximate flowpipe. The basic idea of PBT is that for each segment of a flowpipe, a coarse box which is big enough to contain the segment is constructed using sampled simulation and then in the box we compute by linear programming a set of barrier functions (called barrier tube or BT for short) which work together to form a tube surrounding the flowpipe. The benefit of using PBT is that (1) BT is independent of time and hence can avoid being stretched and deformed by time; and (2) a small number of BTs can form a tight over-approximation for the flowpipe, which means that the computation required to decide whether the BTs intersect the unsafe set can be reduced significantly. We implemented a prototype called PBTS in C++. Experiments on some benchmark systems show that our approach is effective."}],"_id":"142","author":[{"last_name":"Kong","full_name":"Kong, Hui","first_name":"Hui","id":"3BDE25AA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-3066-6941"},{"last_name":"Bartocci","full_name":"Bartocci, Ezio","first_name":"Ezio"},{"orcid":"0000−0002−2985−7724","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","full_name":"Henzinger, Thomas A"}],"title":"Reachable set over-approximation for nonlinear systems using piecewise barrier tubes","status":"public","acknowledgement":"Austrian Science Fund FWF: S11402-N23, S11405-N23, Z211-N32","publication_status":"published","project":[{"call_identifier":"FWF","name":"Rigorous Systems Engineering","grant_number":"S 11407_N23","_id":"25832EC2-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","name":"The Wittgenstein Prize","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211"}],"conference":{"name":"CAV: Computer Aided Verification","end_date":"2018-07-17","location":"Oxford, United Kingdom","start_date":"2018-07-14"},"oa_version":"Published Version","month":"07","ddc":["000"],"file_date_updated":"2020-07-14T12:44:53Z","day":"18","citation":{"chicago":"Kong, Hui, Ezio Bartocci, and Thomas A Henzinger. “Reachable Set Over-Approximation for Nonlinear Systems Using Piecewise Barrier Tubes,” 10981:449–67. Springer, 2018. <a href=\"https://doi.org/10.1007/978-3-319-96145-3_24\">https://doi.org/10.1007/978-3-319-96145-3_24</a>.","mla":"Kong, Hui, et al. <i>Reachable Set Over-Approximation for Nonlinear Systems Using Piecewise Barrier Tubes</i>. Vol. 10981, Springer, 2018, pp. 449–67, doi:<a href=\"https://doi.org/10.1007/978-3-319-96145-3_24\">10.1007/978-3-319-96145-3_24</a>.","ieee":"H. Kong, E. Bartocci, and T. A. Henzinger, “Reachable set over-approximation for nonlinear systems using piecewise barrier tubes,” presented at the CAV: Computer Aided Verification, Oxford, United Kingdom, 2018, vol. 10981, pp. 449–467.","apa":"Kong, H., Bartocci, E., &#38; Henzinger, T. A. (2018). Reachable set over-approximation for nonlinear systems using piecewise barrier tubes (Vol. 10981, pp. 449–467). Presented at the CAV: Computer Aided Verification, Oxford, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-319-96145-3_24\">https://doi.org/10.1007/978-3-319-96145-3_24</a>","ista":"Kong H, Bartocci E, Henzinger TA. 2018. Reachable set over-approximation for nonlinear systems using piecewise barrier tubes. CAV: Computer Aided Verification, LNCS, vol. 10981, 449–467.","short":"H. Kong, E. Bartocci, T.A. Henzinger, in:, Springer, 2018, pp. 449–467.","ama":"Kong H, Bartocci E, Henzinger TA. Reachable set over-approximation for nonlinear systems using piecewise barrier tubes. In: Vol 10981. Springer; 2018:449-467. doi:<a href=\"https://doi.org/10.1007/978-3-319-96145-3_24\">10.1007/978-3-319-96145-3_24</a>"},"article_processing_charge":"No","volume":10981,"has_accepted_license":"1","file":[{"file_id":"5718","date_created":"2018-12-17T15:57:06Z","access_level":"open_access","checksum":"fd95e8026deacef3dc752a733bb9355f","content_type":"application/pdf","date_updated":"2020-07-14T12:44:53Z","file_name":"2018_LNCS_Kong.pdf","file_size":5591566,"relation":"main_file","creator":"dernst"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"year":"2018","alternative_title":["LNCS"],"oa":1,"page":"449 - 467","date_updated":"2023-09-15T12:12:08Z","scopus_import":"1","date_created":"2018-12-11T11:44:51Z","external_id":{"isi":["000491481600024"]},"date_published":"2018-07-18T00:00:00Z","publist_id":"7781","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","department":[{"_id":"ToHe"}],"language":[{"iso":"eng"}],"quality_controlled":"1","type":"conference","isi":1,"intvolume":"     10981","publisher":"Springer"},{"quality_controlled":"1","language":[{"iso":"eng"}],"type":"conference","publisher":"ML Research Press","intvolume":"        84","main_file_link":[{"url":"https://arxiv.org/abs/1708.01733","open_access":"1"}],"date_created":"2023-08-22T14:15:20Z","scopus_import":"1","extern":"1","external_id":{"arxiv":["1708.01733"]},"date_published":"2018-04-15T00:00:00Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"page":"464-472","date_updated":"2023-09-13T07:52:40Z","publication":"Proceedings of the 21st International Conference on Artificial Intelligence and Statistics","alternative_title":["PMLR"],"year":"2018","oa":1,"volume":84,"article_processing_charge":"No","arxiv":1,"oa_version":"Preprint","conference":{"end_date":"2018-04-11","start_date":"2018-04-09","location":"Playa Blanca, Lanzarote","name":"AISTATS: Conference on Artificial Intelligence and Statistics"},"month":"04","citation":{"mla":"Locatello, Francesco, et al. “Boosting Variational Inference: An Optimization Perspective.” <i>Proceedings of the 21st International Conference on Artificial Intelligence and Statistics</i>, vol. 84, ML Research Press, 2018, pp. 464–72.","chicago":"Locatello, Francesco, Rajiv Khanna, Joydeep Ghosh, and Gunnar Rätsch. “Boosting Variational Inference: An Optimization Perspective.” In <i>Proceedings of the 21st International Conference on Artificial Intelligence and Statistics</i>, 84:464–72. ML Research Press, 2018.","ieee":"F. Locatello, R. Khanna, J. Ghosh, and G. Rätsch, “Boosting variational inference: An optimization perspective,” in <i>Proceedings of the 21st International Conference on Artificial Intelligence and Statistics</i>, Playa Blanca, Lanzarote, 2018, vol. 84, pp. 464–472.","apa":"Locatello, F., Khanna, R., Ghosh, J., &#38; Rätsch, G. (2018). Boosting variational inference: An optimization perspective. In <i>Proceedings of the 21st International Conference on Artificial Intelligence and Statistics</i> (Vol. 84, pp. 464–472). Playa Blanca, Lanzarote: ML Research Press.","ama":"Locatello F, Khanna R, Ghosh J, Rätsch G. Boosting variational inference: An optimization perspective. In: <i>Proceedings of the 21st International Conference on Artificial Intelligence and Statistics</i>. Vol 84. ML Research Press; 2018:464-472.","ista":"Locatello F, Khanna R, Ghosh J, Rätsch G. 2018. Boosting variational inference: An optimization perspective. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 84, 464–472.","short":"F. Locatello, R. Khanna, J. Ghosh, G. Rätsch, in:, Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, ML Research Press, 2018, pp. 464–472."},"day":"15","publication_status":"published","status":"public","abstract":[{"text":"Variational inference is a popular technique to approximate a possibly\r\nintractable Bayesian posterior with a more tractable one. Recently, boosting\r\nvariational inference has been proposed as a new paradigm to approximate the\r\nposterior by a mixture of densities by greedily adding components to the\r\nmixture. However, as is the case with many other variational inference\r\nalgorithms, its theoretical properties have not been studied. In the present\r\nwork, we study the convergence properties of this approach from a modern\r\noptimization viewpoint by establishing connections to the classic Frank-Wolfe\r\nalgorithm. Our analyses yields novel theoretical insights regarding the\r\nsufficient conditions for convergence, explicit rates, and algorithmic\r\nsimplifications. Since a lot of focus in previous works for variational\r\ninference has been on tractability, our work is especially important as a much\r\nneeded attempt to bridge the gap between probabilistic models and their\r\ncorresponding theoretical properties.","lang":"eng"}],"_id":"14201","title":"Boosting variational inference: An optimization perspective","author":[{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","full_name":"Locatello, Francesco","last_name":"Locatello","orcid":"0000-0002-4850-0683"},{"full_name":"Khanna, Rajiv","last_name":"Khanna","first_name":"Rajiv"},{"first_name":"Joydeep","full_name":"Ghosh, Joydeep","last_name":"Ghosh"},{"last_name":"Rätsch","full_name":"Rätsch, Gunnar","first_name":"Gunnar"}]},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"date_created":"2023-08-22T14:15:40Z","scopus_import":"1","date_published":"2018-06-06T00:00:00Z","external_id":{"arxiv":["1806.02185"]},"extern":"1","publisher":"Neural Information Processing Systems Foundation","main_file_link":[{"url":"https://arxiv.org/abs/1806.02185","open_access":"1"}],"intvolume":"        31","type":"conference","language":[{"iso":"eng"}],"quality_controlled":"1","oa":1,"year":"2018","date_updated":"2023-09-13T07:38:24Z","publication":"Advances in Neural Information Processing Systems","month":"06","citation":{"chicago":"Locatello, Francesco, Gideon Dresdner, Rajiv Khanna, Isabel Valera, and Gunnar Rätsch. “Boosting Black Box Variational Inference.” In <i>Advances in Neural Information Processing Systems</i>, Vol. 31. Neural Information Processing Systems Foundation, 2018.","mla":"Locatello, Francesco, et al. “Boosting Black Box Variational Inference.” <i>Advances in Neural Information Processing Systems</i>, vol. 31, Neural Information Processing Systems Foundation, 2018.","ama":"Locatello F, Dresdner G, Khanna R, Valera I, Rätsch G. Boosting black box variational inference. In: <i>Advances in Neural Information Processing Systems</i>. Vol 31. Neural Information Processing Systems Foundation; 2018.","ista":"Locatello F, Dresdner G, Khanna R, Valera I, Rätsch G. 2018. Boosting black box variational inference. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 31.","short":"F. Locatello, G. Dresdner, R. Khanna, I. Valera, G. Rätsch, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2018.","apa":"Locatello, F., Dresdner, G., Khanna, R., Valera, I., &#38; Rätsch, G. (2018). Boosting black box variational inference. In <i>Advances in Neural Information Processing Systems</i> (Vol. 31). Montreal, Canada: Neural Information Processing Systems Foundation.","ieee":"F. Locatello, G. Dresdner, R. Khanna, I. Valera, and G. Rätsch, “Boosting black box variational inference,” in <i>Advances in Neural Information Processing Systems</i>, Montreal, Canada, 2018, vol. 31."},"day":"06","oa_version":"Preprint","conference":{"start_date":"2018-12-03","location":"Montreal, Canada","end_date":"2018-12-08","name":"NeurIPS: Neural Information Processing Systems"},"arxiv":1,"volume":31,"article_processing_charge":"No","_id":"14202","title":"Boosting black box variational inference","author":[{"orcid":"0000-0002-4850-0683","last_name":"Locatello","full_name":"Locatello, Francesco","first_name":"Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"first_name":"Gideon","last_name":"Dresdner","full_name":"Dresdner, Gideon"},{"full_name":"Khanna, Rajiv","last_name":"Khanna","first_name":"Rajiv"},{"first_name":"Isabel","last_name":"Valera","full_name":"Valera, Isabel"},{"full_name":"Rätsch, Gunnar","last_name":"Rätsch","first_name":"Gunnar"}],"abstract":[{"text":"Approximating a probability density in a tractable manner is a central task\r\nin Bayesian statistics. Variational Inference (VI) is a popular technique that\r\nachieves tractability by choosing a relatively simple variational family.\r\nBorrowing ideas from the classic boosting framework, recent approaches attempt\r\nto \\emph{boost} VI by replacing the selection of a single density with a\r\ngreedily constructed mixture of densities. In order to guarantee convergence,\r\nprevious works impose stringent assumptions that require significant effort for\r\npractitioners. Specifically, they require a custom implementation of the greedy\r\nstep (called the LMO) for every probabilistic model with respect to an\r\nunnatural variational family of truncated distributions. Our work fixes these\r\nissues with novel theoretical and algorithmic insights. On the theoretical\r\nside, we show that boosting VI satisfies a relaxed smoothness assumption which\r\nis sufficient for the convergence of the functional Frank-Wolfe (FW) algorithm.\r\nFurthermore, we rephrase the LMO problem and propose to maximize the Residual\r\nELBO (RELBO) which replaces the standard ELBO optimization in VI. These\r\ntheoretical enhancements allow for black box implementation of the boosting\r\nsubroutine. Finally, we present a stopping criterion drawn from the duality gap\r\nin the classic FW analyses and exhaustive experiments to illustrate the\r\nusefulness of our theoretical and algorithmic contributions.","lang":"eng"}],"publication_identifier":{"isbn":["9781510884472"],"eissn":["1049-5258"]},"publication_status":"published","status":"public"},{"date_updated":"2023-09-13T08:13:39Z","publication":"Proceedings of the 35th International Conference on Machine Learning","page":"5727-5736","oa":1,"year":"2018","alternative_title":["PMLR"],"intvolume":"        80","main_file_link":[{"url":"https://arxiv.org/abs/1804.08544","open_access":"1"}],"publisher":"ML Research Press","quality_controlled":"1","type":"conference","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"date_created":"2023-08-22T14:16:01Z","external_id":{"arxiv":["1804.08544"]},"date_published":"2018-07-15T00:00:00Z","extern":"1","status":"public","publication_status":"published","_id":"14203","author":[{"full_name":"Yurtsever, Alp","last_name":"Yurtsever","first_name":"Alp"},{"last_name":"Fercoq","full_name":"Fercoq, Olivier","first_name":"Olivier"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","full_name":"Locatello, Francesco","last_name":"Locatello","orcid":"0000-0002-4850-0683"},{"last_name":"Cevher","full_name":"Cevher, Volkan","first_name":"Volkan"}],"title":"A conditional gradient framework for composite convex minimization with applications to semidefinite programming","abstract":[{"text":"We propose a conditional gradient framework for a composite convex minimization template with broad applications. Our approach combines smoothing and homotopy techniques under the CGM framework, and provably achieves the optimal O(1/k−−√) convergence rate. We demonstrate that the same rate holds if the linear subproblems are solved approximately with additive or multiplicative error. In contrast with the relevant work, we are able to characterize the convergence when the non-smooth term is an indicator function. Specific applications of our framework include the non-smooth minimization, semidefinite programming, and minimization with linear inclusion constraints over a compact domain. Numerical evidence demonstrates the benefits of our framework.","lang":"eng"}],"arxiv":1,"article_processing_charge":"No","volume":80,"month":"07","day":"15","citation":{"mla":"Yurtsever, Alp, et al. “A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming.” <i>Proceedings of the 35th International Conference on Machine Learning</i>, vol. 80, ML Research Press, 2018, pp. 5727–36.","chicago":"Yurtsever, Alp, Olivier Fercoq, Francesco Locatello, and Volkan Cevher. “A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming.” In <i>Proceedings of the 35th International Conference on Machine Learning</i>, 80:5727–36. ML Research Press, 2018.","ieee":"A. Yurtsever, O. Fercoq, F. Locatello, and V. Cevher, “A conditional gradient framework for composite convex minimization with applications to semidefinite programming,” in <i>Proceedings of the 35th International Conference on Machine Learning</i>, Stockholm, Sweden, 2018, vol. 80, pp. 5727–5736.","apa":"Yurtsever, A., Fercoq, O., Locatello, F., &#38; Cevher, V. (2018). A conditional gradient framework for composite convex minimization with applications to semidefinite programming. In <i>Proceedings of the 35th International Conference on Machine Learning</i> (Vol. 80, pp. 5727–5736). Stockholm, Sweden: ML Research Press.","ama":"Yurtsever A, Fercoq O, Locatello F, Cevher V. A conditional gradient framework for composite convex minimization with applications to semidefinite programming. In: <i>Proceedings of the 35th International Conference on Machine Learning</i>. Vol 80. ML Research Press; 2018:5727-5736.","short":"A. Yurtsever, O. Fercoq, F. Locatello, V. Cevher, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 5727–5736.","ista":"Yurtsever A, Fercoq O, Locatello F, Cevher V. 2018. A conditional gradient framework for composite convex minimization with applications to semidefinite programming. Proceedings of the 35th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 80, 5727–5736."},"conference":{"end_date":"2018-07-15","location":"Stockholm, Sweden","start_date":"2018-07-10","name":"ICML: International Conference on Machine Learning"},"oa_version":"Preprint"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"date_created":"2023-08-22T14:16:25Z","scopus_import":"1","date_published":"2018-07-01T00:00:00Z","external_id":{"arxiv":["1803.09539"]},"extern":"1","publisher":"ML Research Press","intvolume":"        80","main_file_link":[{"url":"https://arxiv.org/abs/1803.09539","open_access":"1"}],"quality_controlled":"1","language":[{"iso":"eng"}],"type":"conference","oa":1,"year":"2018","alternative_title":["PMLR"],"date_updated":"2023-09-13T08:19:05Z","publication":"Proceedings of the 35th International Conference on Machine Learning","page":"3198-3207","month":"07","citation":{"ista":"Locatello F, Raj A, Karimireddy SP, Rätsch G, Schölkopf B, Stich SU, Jaggi M. 2018. On matching pursuit and coordinate descent. Proceedings of the 35th International Conference on Machine Learning. , PMLR, vol. 80, 3198–3207.","short":"F. Locatello, A. Raj, S.P. Karimireddy, G. Rätsch, B. Schölkopf, S.U. Stich, M. Jaggi, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 3198–3207.","ama":"Locatello F, Raj A, Karimireddy SP, et al. On matching pursuit and coordinate descent. In: <i>Proceedings of the 35th International Conference on Machine Learning</i>. Vol 80. ML Research Press; 2018:3198-3207.","ieee":"F. Locatello <i>et al.</i>, “On matching pursuit and coordinate descent,” in <i>Proceedings of the 35th International Conference on Machine Learning</i>, 2018, vol. 80, pp. 3198–3207.","apa":"Locatello, F., Raj, A., Karimireddy, S. P., Rätsch, G., Schölkopf, B., Stich, S. U., &#38; Jaggi, M. (2018). On matching pursuit and coordinate descent. In <i>Proceedings of the 35th International Conference on Machine Learning</i> (Vol. 80, pp. 3198–3207). ML Research Press.","mla":"Locatello, Francesco, et al. “On Matching Pursuit and Coordinate Descent.” <i>Proceedings of the 35th International Conference on Machine Learning</i>, vol. 80, ML Research Press, 2018, pp. 3198–207.","chicago":"Locatello, Francesco, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, and Martin Jaggi. “On Matching Pursuit and Coordinate Descent.” In <i>Proceedings of the 35th International Conference on Machine Learning</i>, 80:3198–3207. ML Research Press, 2018."},"day":"01","oa_version":"Preprint","arxiv":1,"volume":80,"article_processing_charge":"No","_id":"14204","title":"On matching pursuit and coordinate descent","author":[{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","full_name":"Locatello, Francesco","last_name":"Locatello","orcid":"0000-0002-4850-0683"},{"first_name":"Anant","last_name":"Raj","full_name":"Raj, Anant"},{"first_name":"Sai Praneeth","last_name":"Karimireddy","full_name":"Karimireddy, Sai Praneeth"},{"full_name":"Rätsch, Gunnar","last_name":"Rätsch","first_name":"Gunnar"},{"first_name":"Bernhard","last_name":"Schölkopf","full_name":"Schölkopf, Bernhard"},{"full_name":"Stich, Sebastian U.","last_name":"Stich","first_name":"Sebastian U."},{"first_name":"Martin","last_name":"Jaggi","full_name":"Jaggi, Martin"}],"abstract":[{"lang":"eng","text":"Two popular examples of first-order optimization methods over linear spaces are coordinate descent and matching pursuit algorithms, with their randomized variants. While the former targets the optimization by moving along coordinates, the latter considers a generalized notion of directions. Exploiting the connection between the two algorithms, we present a unified analysis of both, providing affine invariant sublinear O(1/t) rates on smooth objectives and linear convergence on strongly convex objectives. As a byproduct of our affine invariant analysis of matching pursuit, our rates for steepest coordinate descent are the tightest known. Furthermore, we show the first accelerated convergence rate O(1/t2) for matching pursuit and steepest coordinate descent on convex objectives."}],"status":"public","publication_status":"published"},{"_id":"14224","oa":1,"title":"Clustering meets implicit generative models","author":[{"full_name":"Locatello, Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","orcid":"0000-0002-4850-0683"},{"last_name":"Vincent","full_name":"Vincent, Damien","first_name":"Damien"},{"first_name":"Ilya","last_name":"Tolstikhin","full_name":"Tolstikhin, Ilya"},{"first_name":"Gunnar","last_name":"Ratsch","full_name":"Ratsch, Gunnar"},{"first_name":"Sylvain","full_name":"Gelly, Sylvain","last_name":"Gelly"},{"first_name":"Bernhard","last_name":"Scholkopf","full_name":"Scholkopf, Bernhard"}],"abstract":[{"lang":"eng","text":"Clustering is a cornerstone of unsupervised learning which can be thought as disentangling multiple generative mechanisms underlying the data. In this paper we introduce an algorithmic framework to train mixtures of implicit generative models which we particularize for variational autoencoders. Relying on an additional set of discriminators, we propose a competitive procedure in which the models only need to approximate the portion of the data distribution from which they can produce realistic samples. As a byproduct, each model is simpler to train, and a clustering interpretation arises naturally from the partitioning of the training points among the models. We empirically show that our approach splits the training distribution in a reasonable way and increases the quality of the generated samples."}],"year":"2018","date_updated":"2023-09-13T09:08:24Z","publication":"6th International Conference on Learning Representations","status":"public","publication_status":"published","month":"05","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ama":"Locatello F, Vincent D, Tolstikhin I, Ratsch G, Gelly S, Scholkopf B. Clustering meets implicit generative models. In: <i>6th International Conference on Learning Representations</i>. ; 2018.","short":"F. Locatello, D. Vincent, I. Tolstikhin, G. Ratsch, S. Gelly, B. Scholkopf, in:, 6th International Conference on Learning Representations, 2018.","ista":"Locatello F, Vincent D, Tolstikhin I, Ratsch G, Gelly S, Scholkopf B. 2018. Clustering meets implicit generative models. 6th International Conference on Learning Representations. International Conference on Machine Learning.","apa":"Locatello, F., Vincent, D., Tolstikhin, I., Ratsch, G., Gelly, S., &#38; Scholkopf, B. (2018). Clustering meets implicit generative models. In <i>6th International Conference on Learning Representations</i>. Vancouver, Canada.","ieee":"F. Locatello, D. Vincent, I. Tolstikhin, G. Ratsch, S. Gelly, and B. Scholkopf, “Clustering meets implicit generative models,” in <i>6th International Conference on Learning Representations</i>, Vancouver, Canada, 2018.","mla":"Locatello, Francesco, et al. “Clustering Meets Implicit Generative Models.” <i>6th International Conference on Learning Representations</i>, 2018.","chicago":"Locatello, Francesco, Damien Vincent, Ilya Tolstikhin, Gunnar Ratsch, Sylvain Gelly, and Bernhard Scholkopf. “Clustering Meets Implicit Generative Models.” In <i>6th International Conference on Learning Representations</i>, 2018."},"department":[{"_id":"FrLo"}],"day":"01","date_created":"2023-08-22T14:25:34Z","oa_version":"Preprint","conference":{"name":"International Conference on Machine Learning","end_date":"2018-05-03","start_date":"2018-04-30","location":"Vancouver, Canada"},"scopus_import":"1","extern":"1","date_published":"2018-05-01T00:00:00Z","external_id":{"arxiv":["1804.11130"]},"arxiv":1,"main_file_link":[{"url":"https://arxiv.org/abs/1804.11130","open_access":"1"}],"article_processing_charge":"No","type":"conference","quality_controlled":"1","language":[{"iso":"eng"}]},{"oa_version":"Preprint","conference":{"start_date":"2018-07-09","location":"Oxford, United Kingdom","end_date":"2018-07-12","name":"LICS: Logic in Computer Science"},"month":"07","citation":{"chicago":"Brázdil, Tomáš, Krishnendu Chatterjee, Antonín Kučera, Petr Novotný, Dominik Velan, and Florian Zuleger. “Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS,” F138033:185–94. IEEE, 2018. <a href=\"https://doi.org/10.1145/3209108.3209191\">https://doi.org/10.1145/3209108.3209191</a>.","mla":"Brázdil, Tomáš, et al. <i>Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS</i>. Vol. F138033, IEEE, 2018, pp. 185–94, doi:<a href=\"https://doi.org/10.1145/3209108.3209191\">10.1145/3209108.3209191</a>.","ama":"Brázdil T, Chatterjee K, Kučera A, Novotný P, Velan D, Zuleger F. Efficient algorithms for asymptotic bounds on termination time in VASS. In: Vol F138033. IEEE; 2018:185-194. doi:<a href=\"https://doi.org/10.1145/3209108.3209191\">10.1145/3209108.3209191</a>","ista":"Brázdil T, Chatterjee K, Kučera A, Novotný P, Velan D, Zuleger F. 2018. Efficient algorithms for asymptotic bounds on termination time in VASS. LICS: Logic in Computer Science, ACM/IEEE Symposium on Logic in Computer Science, vol. F138033, 185–194.","short":"T. Brázdil, K. Chatterjee, A. Kučera, P. Novotný, D. Velan, F. Zuleger, in:, IEEE, 2018, pp. 185–194.","apa":"Brázdil, T., Chatterjee, K., Kučera, A., Novotný, P., Velan, D., &#38; Zuleger, F. (2018). Efficient algorithms for asymptotic bounds on termination time in VASS (Vol. F138033, pp. 185–194). Presented at the LICS: Logic in Computer Science, Oxford, United Kingdom: IEEE. <a href=\"https://doi.org/10.1145/3209108.3209191\">https://doi.org/10.1145/3209108.3209191</a>","ieee":"T. Brázdil, K. Chatterjee, A. Kučera, P. Novotný, D. Velan, and F. Zuleger, “Efficient algorithms for asymptotic bounds on termination time in VASS,” presented at the LICS: Logic in Computer Science, Oxford, United Kingdom, 2018, vol. F138033, pp. 185–194."},"day":"09","article_processing_charge":"No","volume":"F138033","doi":"10.1145/3209108.3209191","abstract":[{"lang":"eng","text":"Vector Addition Systems with States (VASS) provide a well-known and fundamental model for the analysis of concurrent processes, parameterized systems, and are also used as abstract models of programs in resource bound analysis. In this paper we study the problem of obtaining asymptotic bounds on the termination time of a given VASS. In particular, we focus on the practically important case of obtaining polynomial bounds on termination time. Our main contributions are as follows: First, we present a polynomial-time algorithm for deciding whether a given VASS has a linear asymptotic complexity. We also show that if the complexity of a VASS is not linear, it is at least quadratic. Second, we classify VASS according to quantitative properties of their cycles. We show that certain singularities in these properties are the key reason for non-polynomial asymptotic complexity of VASS. In absence of singularities, we show that the asymptotic complexity is always polynomial and of the form Θ(nk), for some integer k d, where d is the dimension of the VASS. We present a polynomial-time algorithm computing the optimal k. For general VASS, the same algorithm, which is based on a complete technique for the construction of ranking functions in VASS, produces a valid lower bound, i.e., a k such that the termination complexity is (nk). Our results are based on new insights into the geometry of VASS dynamics, which hold the potential for further applicability to VASS analysis."}],"_id":"143","title":"Efficient algorithms for asymptotic bounds on termination time in VASS","author":[{"last_name":"Brázdil","full_name":"Brázdil, Tomáš","first_name":"Tomáš"},{"full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","first_name":"Krishnendu","orcid":"0000-0002-4561-241X"},{"first_name":"Antonín","full_name":"Kučera, Antonín","last_name":"Kučera"},{"full_name":"Novotny, Petr","last_name":"Novotny","id":"3CC3B868-F248-11E8-B48F-1D18A9856A87","first_name":"Petr"},{"first_name":"Dominik","last_name":"Velan","full_name":"Velan, Dominik"},{"first_name":"Florian","full_name":"Zuleger, Florian","last_name":"Zuleger"}],"ec_funded":1,"status":"public","publication_status":"published","project":[{"grant_number":"ICT15-003","_id":"25892FC0-B435-11E9-9278-68D0E5697425","name":"Efficient Algorithms for Computer Aided Verification"},{"call_identifier":"FP7","name":"Quantitative Graph Games: Theory and Applications","grant_number":"279307","_id":"2581B60A-B435-11E9-9278-68D0E5697425"},{"_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","call_identifier":"FWF"}],"publication_identifier":{"isbn":["978-1-4503-5583-4"]},"date_created":"2018-12-11T11:44:51Z","scopus_import":"1","external_id":{"isi":["000545262800020"]},"date_published":"2018-07-09T00:00:00Z","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publist_id":"7780","department":[{"_id":"KrCh"}],"language":[{"iso":"eng"}],"type":"conference","quality_controlled":"1","isi":1,"publisher":"IEEE","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1804.10985"}],"year":"2018","alternative_title":["ACM/IEEE Symposium on Logic in Computer Science"],"oa":1,"page":"185 - 194","date_updated":"2025-06-02T08:53:48Z"}]