[{"main_file_link":[{"url":"https://arxiv.org/abs/2006.14908","open_access":"1"}],"doi":"10.1007/978-3-030-68766-3_28","publication":"28th International Symposium on Graph Drawing and Network Visualization","oa_version":"Preprint","volume":12590,"date_created":"2021-03-28T22:01:44Z","status":"public","day":"20","series_title":"LNCS","page":"359-371","external_id":{"arxiv":["2006.14908"]},"conference":{"end_date":"2020-09-18","start_date":"2020-09-16","name":"GD: Graph Drawing and Network Visualization","location":"Virtual, Online"},"year":"2020","intvolume":" 12590","month":"09","date_published":"2020-09-20T00:00:00Z","acknowledgement":"Supported by the National Research, Development and Innovation Office, NKFIH, KKP-133864, K-131529, K-116769, K-132696, by the Higher Educational Institutional Excellence Program 2019 NKFIH-1158-6/2019, the Austrian Science Fund (FWF), grant Z 342-N31, by the Ministry of Education and Science of the Russian Federation MegaGrant No. 075-15-2019-1926, and by the ERC Synergy Grant “Dynasnet” No. 810115. A full version can be found at https://arxiv.org/abs/2006.14908.","date_updated":"2021-04-06T11:32:32Z","oa":1,"project":[{"_id":"268116B8-B435-11E9-9278-68D0E5697425","name":"The Wittgenstein Prize","call_identifier":"FWF","grant_number":"Z00342"}],"publication_status":"published","publication_identifier":{"issn":["0302-9743"],"eissn":["1611-3349"],"isbn":["9783030687656"]},"citation":{"chicago":"Pach, János, Gábor Tardos, and Géza Tóth. “Crossings between Non-Homotopic Edges.” In 28th International Symposium on Graph Drawing and Network Visualization, 12590:359–71. LNCS. Springer Nature, 2020. https://doi.org/10.1007/978-3-030-68766-3_28.","ama":"Pach J, Tardos G, Tóth G. Crossings between non-homotopic edges. In: 28th International Symposium on Graph Drawing and Network Visualization. Vol 12590. LNCS. Springer Nature; 2020:359-371. doi:10.1007/978-3-030-68766-3_28","short":"J. Pach, G. Tardos, G. Tóth, in:, 28th International Symposium on Graph Drawing and Network Visualization, Springer Nature, 2020, pp. 359–371.","ista":"Pach J, Tardos G, Tóth G. 2020. Crossings between non-homotopic edges. 28th International Symposium on Graph Drawing and Network Visualization. GD: Graph Drawing and Network VisualizationLNCS vol. 12590, 359–371.","ieee":"J. Pach, G. Tardos, and G. Tóth, “Crossings between non-homotopic edges,” in 28th International Symposium on Graph Drawing and Network Visualization, Virtual, Online, 2020, vol. 12590, pp. 359–371.","mla":"Pach, János, et al. “Crossings between Non-Homotopic Edges.” 28th International Symposium on Graph Drawing and Network Visualization, vol. 12590, Springer Nature, 2020, pp. 359–71, doi:10.1007/978-3-030-68766-3_28.","apa":"Pach, J., Tardos, G., & Tóth, G. (2020). Crossings between non-homotopic edges. In 28th International Symposium on Graph Drawing and Network Visualization (Vol. 12590, pp. 359–371). Virtual, Online: Springer Nature. https://doi.org/10.1007/978-3-030-68766-3_28"},"type":"conference","scopus_import":"1","arxiv":1,"abstract":[{"lang":"eng","text":"We call a multigraph non-homotopic if it can be drawn in the plane in such a way that no two edges connecting the same pair of vertices can be continuously transformed into each other without passing through a vertex, and no loop can be shrunk to its end-vertex in the same way. It is easy to see that a non-homotopic multigraph on n>1 vertices can have arbitrarily many edges. We prove that the number of crossings between the edges of a non-homotopic multigraph with n vertices and m>4n edges is larger than cm2n for some constant c>0 , and that this bound is tight up to a polylogarithmic factor. We also show that the lower bound is not asymptotically sharp as n is fixed and m⟶∞ ."}],"_id":"9299","quality_controlled":"1","article_processing_charge":"No","department":[{"_id":"HeEd"}],"language":[{"iso":"eng"}],"publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Crossings between non-homotopic edges","author":[{"full_name":"Pach, János","last_name":"Pach","first_name":"János","id":"E62E3130-B088-11EA-B919-BF823C25FEA4"},{"last_name":"Tardos","first_name":"Gábor","full_name":"Tardos, Gábor"},{"last_name":"Tóth","first_name":"Géza","full_name":"Tóth, Géza"}]},{"date_created":"2021-04-04T22:01:22Z","status":"public","day":"01","volume":75,"related_material":{"record":[{"id":"8183","relation":"earlier_version","status":"public"},{"id":"10220","status":"public","relation":"later_version"}]},"isi":1,"oa_version":"Preprint","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1511.03501"}],"doi":"10.1070/RM9943","publication":"Russian Mathematical Surveys","date_updated":"2023-08-14T11:43:54Z","issue":"6","oa":1,"intvolume":" 75","month":"12","date_published":"2020-12-01T00:00:00Z","acknowledgement":"This research was carried out with the support of the Russian Foundation for Basic Research(grant no. 19-01-00169)","year":"2020","external_id":{"arxiv":["1511.03501"],"isi":["000625983100001"]},"page":"1156-1158","_id":"9308","quality_controlled":"1","citation":{"short":"S. Avvakumov, U. Wagner, I. Mabillard, A.B. Skopenkov, Russian Mathematical Surveys 75 (2020) 1156–1158.","ista":"Avvakumov S, Wagner U, Mabillard I, Skopenkov AB. 2020. Eliminating higher-multiplicity intersections, III. Codimension 2. Russian Mathematical Surveys. 75(6), 1156–1158.","ieee":"S. Avvakumov, U. Wagner, I. Mabillard, and A. B. Skopenkov, “Eliminating higher-multiplicity intersections, III. Codimension 2,” Russian Mathematical Surveys, vol. 75, no. 6. IOP Publishing, pp. 1156–1158, 2020.","ama":"Avvakumov S, Wagner U, Mabillard I, Skopenkov AB. Eliminating higher-multiplicity intersections, III. Codimension 2. Russian Mathematical Surveys. 2020;75(6):1156-1158. doi:10.1070/RM9943","chicago":"Avvakumov, Sergey, Uli Wagner, Isaac Mabillard, and A. B. Skopenkov. “Eliminating Higher-Multiplicity Intersections, III. Codimension 2.” Russian Mathematical Surveys. IOP Publishing, 2020. https://doi.org/10.1070/RM9943.","apa":"Avvakumov, S., Wagner, U., Mabillard, I., & Skopenkov, A. B. (2020). Eliminating higher-multiplicity intersections, III. Codimension 2. Russian Mathematical Surveys. IOP Publishing. https://doi.org/10.1070/RM9943","mla":"Avvakumov, Sergey, et al. “Eliminating Higher-Multiplicity Intersections, III. Codimension 2.” Russian Mathematical Surveys, vol. 75, no. 6, IOP Publishing, 2020, pp. 1156–58, doi:10.1070/RM9943."},"publication_identifier":{"issn":["0036-0279"]},"type":"journal_article","arxiv":1,"scopus_import":"1","publication_status":"published","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"full_name":"Avvakumov, Sergey","last_name":"Avvakumov","id":"3827DAC8-F248-11E8-B48F-1D18A9856A87","first_name":"Sergey"},{"first_name":"Uli","id":"36690CA2-F248-11E8-B48F-1D18A9856A87","last_name":"Wagner","orcid":"0000-0002-1494-0568","full_name":"Wagner, Uli"},{"full_name":"Mabillard, Isaac","first_name":"Isaac","id":"32BF9DAA-F248-11E8-B48F-1D18A9856A87","last_name":"Mabillard"},{"last_name":"Skopenkov","first_name":"A. B.","full_name":"Skopenkov, A. B."}],"title":"Eliminating higher-multiplicity intersections, III. Codimension 2","publisher":"IOP Publishing","language":[{"iso":"eng"}],"article_type":"original","article_processing_charge":"No","department":[{"_id":"UlWa"}]},{"doi":"10.1021/jacs.9b13450.s002","main_file_link":[{"open_access":"1"}],"related_material":{"record":[{"id":"8040","status":"public","relation":"used_in_publication"}]},"oa_version":"Published Version","citation":{"mla":"Gupta, Chitrak, et al. Charge Transfer and Chemo-Mechanical Coupling in Respiratory Complex I. American Chemical Society, 2020, doi:10.1021/jacs.9b13450.s002.","apa":"Gupta, C., Khaniya, U., Chan, C., Dehez, F., Shekhar, M., Gunner, M. R., … Singharoy, A. (2020). Charge transfer and chemo-mechanical coupling in respiratory complex I. American Chemical Society. https://doi.org/10.1021/jacs.9b13450.s002","chicago":"Gupta, Chitrak, Umesh Khaniya, Chun Chan, Francois Dehez, Mrinal Shekhar, M. R. Gunner, Leonid A Sazanov, Christophe Chipot, and Abhishek Singharoy. “Charge Transfer and Chemo-Mechanical Coupling in Respiratory Complex I.” American Chemical Society, 2020. https://doi.org/10.1021/jacs.9b13450.s002.","short":"C. Gupta, U. Khaniya, C. Chan, F. Dehez, M. Shekhar, M.R. Gunner, L.A. Sazanov, C. Chipot, A. Singharoy, (2020).","ista":"Gupta C, Khaniya U, Chan C, Dehez F, Shekhar M, Gunner MR, Sazanov LA, Chipot C, Singharoy A. 2020. Charge transfer and chemo-mechanical coupling in respiratory complex I, American Chemical Society, 10.1021/jacs.9b13450.s002.","ieee":"C. Gupta et al., “Charge transfer and chemo-mechanical coupling in respiratory complex I.” American Chemical Society, 2020.","ama":"Gupta C, Khaniya U, Chan C, et al. Charge transfer and chemo-mechanical coupling in respiratory complex I. 2020. doi:10.1021/jacs.9b13450.s002"},"abstract":[{"text":"The mitochondrial respiratory chain, formed by five protein complexes, utilizes energy from catabolic processes to synthesize ATP. Complex I, the first and the largest protein complex of the chain, harvests electrons from NADH to reduce quinone, while pumping protons across the mitochondrial membrane. Detailed knowledge of the working principle of such coupled charge-transfer processes remains, however, fragmentary due to bottlenecks in understanding redox-driven conformational transitions and their interplay with the hydrated proton pathways. Complex I from Thermus thermophilus encases 16 subunits with nine iron–sulfur clusters, reduced by electrons from NADH. Here, employing the latest crystal structure of T. thermophilus complex I, we have used microsecond-scale molecular dynamics simulations to study the chemo-mechanical coupling between redox changes of the iron–sulfur clusters and conformational transitions across complex I. First, we identify the redox switches within complex I, which allosterically couple the dynamics of the quinone binding pocket to the site of NADH reduction. Second, our free-energy calculations reveal that the affinity of the quinone, specifically menaquinone, for the binding-site is higher than that of its reduced, menaquinol forma design essential for menaquinol release. Remarkably, the barriers to diffusive menaquinone dynamics are lesser than that of the more ubiquitous ubiquinone, and the naphthoquinone headgroup of the former furnishes stronger binding interactions with the pocket, favoring menaquinone for charge transport in T. thermophilus. Our computations are consistent with experimentally validated mutations and hierarchize the key residues into three functional classes, identifying new mutation targets. Third, long-range hydrogen-bond networks connecting the quinone-binding site to the transmembrane subunits are found to be responsible for proton pumping. Put together, the simulations reveal the molecular design principles linking redox reactions to quinone turnover to proton translocation in complex I.","lang":"eng"}],"type":"research_data_reference","_id":"9326","tmp":{"short":"CC BY-NC (4.0)","name":"Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","image":"/images/cc_by_nc.png"},"date_created":"2021-04-14T12:05:20Z","status":"public","day":"20","article_processing_charge":"No","department":[{"_id":"LeSa"}],"license":"https://creativecommons.org/licenses/by-nc/4.0/","year":"2020","date_published":"2020-05-20T00:00:00Z","month":"05","publisher":"American Chemical Society","date_updated":"2023-08-22T07:49:37Z","author":[{"first_name":"Chitrak","last_name":"Gupta","full_name":"Gupta, Chitrak"},{"full_name":"Khaniya, Umesh","last_name":"Khaniya","first_name":"Umesh"},{"first_name":"Chun","last_name":"Chan","full_name":"Chan, Chun"},{"full_name":"Dehez, Francois","last_name":"Dehez","first_name":"Francois"},{"last_name":"Shekhar","first_name":"Mrinal","full_name":"Shekhar, Mrinal"},{"full_name":"Gunner, M. R.","first_name":"M. R.","last_name":"Gunner"},{"full_name":"Sazanov, Leonid A","last_name":"Sazanov","orcid":"0000-0002-0977-7989","first_name":"Leonid A","id":"338D39FE-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Chipot","first_name":"Christophe","full_name":"Chipot, Christophe"},{"full_name":"Singharoy, Abhishek","first_name":"Abhishek","last_name":"Singharoy"}],"title":"Charge transfer and chemo-mechanical coupling in respiratory complex I","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1},{"publication":"37th International Conference on Machine Learning, ICML 2020","oa_version":"Published Version","volume":119,"date_created":"2021-05-23T22:01:45Z","ddc":["000"],"day":"12","status":"public","page":"5533-5543","conference":{"location":"Online","name":"ICML: International Conference on Machine Learning","end_date":"2020-07-18","start_date":"2020-07-12"},"year":"2020","month":"07","intvolume":" 119","date_published":"2020-07-12T00:00:00Z","date_updated":"2023-02-23T13:57:24Z","oa":1,"citation":{"chicago":"Kurtz, Mark, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William Leiserson, et al. “Inducing and Exploiting Activation Sparsity for Fast Neural Network Inference.” In 37th International Conference on Machine Learning, ICML 2020, 119:5533–43, 2020.","ama":"Kurtz M, Kopinsky J, Gelashvili R, et al. Inducing and exploiting activation sparsity for fast neural network inference. In: 37th International Conference on Machine Learning, ICML 2020. Vol 119. ; 2020:5533-5543.","ieee":"M. Kurtz et al., “Inducing and exploiting activation sparsity for fast neural network inference,” in 37th International Conference on Machine Learning, ICML 2020, Online, 2020, vol. 119, pp. 5533–5543.","ista":"Kurtz M, Kopinsky J, Gelashvili R, Matveev A, Carr J, Goin M, Leiserson W, Moore S, Nell B, Shavit N, Alistarh D-A. 2020. Inducing and exploiting activation sparsity for fast neural network inference. 37th International Conference on Machine Learning, ICML 2020. ICML: International Conference on Machine Learning vol. 119, 5533–5543.","short":"M. Kurtz, J. Kopinsky, R. Gelashvili, A. Matveev, J. Carr, M. Goin, W. Leiserson, S. Moore, B. Nell, N. Shavit, D.-A. Alistarh, in:, 37th International Conference on Machine Learning, ICML 2020, 2020, pp. 5533–5543.","mla":"Kurtz, Mark, et al. “Inducing and Exploiting Activation Sparsity for Fast Neural Network Inference.” 37th International Conference on Machine Learning, ICML 2020, vol. 119, 2020, pp. 5533–43.","apa":"Kurtz, M., Kopinsky, J., Gelashvili, R., Matveev, A., Carr, J., Goin, M., … Alistarh, D.-A. (2020). Inducing and exploiting activation sparsity for fast neural network inference. In 37th International Conference on Machine Learning, ICML 2020 (Vol. 119, pp. 5533–5543). Online."},"publication_identifier":{"issn":["2640-3498"]},"type":"conference","file_date_updated":"2021-05-25T09:51:36Z","scopus_import":"1","abstract":[{"text":"Optimizing convolutional neural networks for fast inference has recently become an extremely active area of research. One of the go-to solutions in this context is weight pruning, which aims to reduce computational and memory footprint by removing large subsets of the connections in a neural network. Surprisingly, much less attention has been given to exploiting sparsity in the activation maps, which tend to be naturally sparse in many settings thanks to the structure of rectified linear (ReLU) activation functions. In this paper, we present an in-depth analysis of methods for maximizing the sparsity of the activations in a trained neural network, and show that, when coupled with an efficient sparse-input convolution algorithm, we can leverage this sparsity for significant performance gains. To induce highly sparse activation maps without accuracy loss, we introduce a new regularization technique, coupled with a new threshold-based sparsification method based on a parameterized activation function called Forced-Activation-Threshold Rectified Linear Unit (FATReLU). We examine the impact of our methods on popular image classification models, showing that most architectures can adapt to significantly sparser activation maps without any accuracy loss. Our second contribution is showing that these these compression gains can be translated into inference speedups: we provide a new algorithm to enable fast convolution operations over networks with sparse activations, and show that it can enable significant speedups for end-to-end inference on a range of popular models on the large-scale ImageNet image classification task on modern Intel CPUs, with little or no retraining cost. ","lang":"eng"}],"_id":"9415","quality_controlled":"1","article_processing_charge":"No","department":[{"_id":"DaAl"}],"language":[{"iso":"eng"}],"has_accepted_license":"1","file":[{"file_name":"2020_PMLR_Kurtz.pdf","success":1,"date_created":"2021-05-25T09:51:36Z","date_updated":"2021-05-25T09:51:36Z","creator":"kschuh","file_size":741899,"file_id":"9421","content_type":"application/pdf","relation":"main_file","checksum":"2aaaa7d7226e49161311d91627cf783b","access_level":"open_access"}],"title":"Inducing and exploiting activation sparsity for fast neural network inference","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Kurtz, Mark","first_name":"Mark","last_name":"Kurtz"},{"first_name":"Justin","last_name":"Kopinsky","full_name":"Kopinsky, Justin"},{"first_name":"Rati","last_name":"Gelashvili","full_name":"Gelashvili, Rati"},{"full_name":"Matveev, Alexander","first_name":"Alexander","last_name":"Matveev"},{"last_name":"Carr","first_name":"John","full_name":"Carr, John"},{"full_name":"Goin, Michael","first_name":"Michael","last_name":"Goin"},{"full_name":"Leiserson, William","first_name":"William","last_name":"Leiserson"},{"full_name":"Moore, Sage","last_name":"Moore","first_name":"Sage"},{"full_name":"Nell, Bill","first_name":"Bill","last_name":"Nell"},{"full_name":"Shavit, Nir","first_name":"Nir","last_name":"Shavit"},{"full_name":"Alistarh, Dan-Adrian","last_name":"Alistarh","orcid":"0000-0003-3650-940X","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian"}]},{"page":"310-323.e7","external_id":{"pmid":["31732458"]},"year":"2020","intvolume":" 77","month":"01","date_published":"2020-01-16T00:00:00Z","issue":"2","oa":1,"date_updated":"2021-12-14T07:51:15Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.molcel.2019.10.011"}],"doi":"10.1016/j.molcel.2019.10.011","publication":"Molecular Cell","oa_version":"Published Version","pmid":1,"volume":77,"day":"16","status":"public","date_created":"2021-06-08T06:37:09Z","department":[{"_id":"DaZi"}],"article_processing_charge":"No","article_type":"original","language":[{"iso":"eng"}],"publisher":"Elsevier","title":"DNA methylation and histone H1 jointly repress transposable elements and aberrant intragenic transcripts","user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"full_name":"Choi, Jaemyung","last_name":"Choi","first_name":"Jaemyung"},{"full_name":"Lyons, David B.","last_name":"Lyons","first_name":"David B."},{"full_name":"Kim, M. Yvonne","last_name":"Kim","first_name":"M. Yvonne"},{"full_name":"Moore, Jonathan D.","first_name":"Jonathan D.","last_name":"Moore"},{"full_name":"Zilberman, Daniel","first_name":"Daniel","id":"6973db13-dd5f-11ea-814e-b3e5455e9ed1","last_name":"Zilberman","orcid":"0000-0002-0123-8649"}],"publication_status":"published","type":"journal_article","scopus_import":"1","abstract":[{"text":"DNA methylation and histone H1 mediate transcriptional silencing of genes and transposable elements, but how they interact is unclear. In plants and animals with mosaic genomic methylation, functionally mysterious methylation is also common within constitutively active housekeeping genes. Here, we show that H1 is enriched in methylated sequences, including genes, of Arabidopsis thaliana, yet this enrichment is independent of DNA methylation. Loss of H1 disperses heterochromatin, globally alters nucleosome organization, and activates H1-bound genes, but only weakly de-represses transposable elements. However, H1 loss strongly activates transposable elements hypomethylated through mutation of DNA methyltransferase MET1. Hypomethylation of genes also activates antisense transcription, which is modestly enhanced by H1 loss. Our results demonstrate that H1 and DNA methylation jointly maintain transcriptional homeostasis by silencing transposable elements and aberrant intragenic transcripts. Such functionality plausibly explains why DNA methylation, a well-known mutagen, has been maintained within coding sequences of crucial plant and animal genes.","lang":"eng"}],"extern":"1","citation":{"ama":"Choi J, Lyons DB, Kim MY, Moore JD, Zilberman D. DNA methylation and histone H1 jointly repress transposable elements and aberrant intragenic transcripts. Molecular Cell. 2020;77(2):310-323.e7. doi:10.1016/j.molcel.2019.10.011","ista":"Choi J, Lyons DB, Kim MY, Moore JD, Zilberman D. 2020. DNA methylation and histone H1 jointly repress transposable elements and aberrant intragenic transcripts. Molecular Cell. 77(2), 310–323.e7.","short":"J. Choi, D.B. Lyons, M.Y. Kim, J.D. Moore, D. Zilberman, Molecular Cell 77 (2020) 310–323.e7.","ieee":"J. Choi, D. B. Lyons, M. Y. Kim, J. D. Moore, and D. Zilberman, “DNA methylation and histone H1 jointly repress transposable elements and aberrant intragenic transcripts,” Molecular Cell, vol. 77, no. 2. Elsevier, p. 310–323.e7, 2020.","chicago":"Choi, Jaemyung, David B. Lyons, M. Yvonne Kim, Jonathan D. Moore, and Daniel Zilberman. “DNA Methylation and Histone H1 Jointly Repress Transposable Elements and Aberrant Intragenic Transcripts.” Molecular Cell. Elsevier, 2020. https://doi.org/10.1016/j.molcel.2019.10.011.","apa":"Choi, J., Lyons, D. B., Kim, M. Y., Moore, J. D., & Zilberman, D. (2020). DNA methylation and histone H1 jointly repress transposable elements and aberrant intragenic transcripts. Molecular Cell. Elsevier. https://doi.org/10.1016/j.molcel.2019.10.011","mla":"Choi, Jaemyung, et al. “DNA Methylation and Histone H1 Jointly Repress Transposable Elements and Aberrant Intragenic Transcripts.” Molecular Cell, vol. 77, no. 2, Elsevier, 2020, p. 310–323.e7, doi:10.1016/j.molcel.2019.10.011."},"publication_identifier":{"eissn":["1097-4164"],"issn":["1097-2765"]},"quality_controlled":"1","_id":"9526"},{"article_processing_charge":"No","article_type":"original","language":[{"iso":"eng"}],"publisher":"Wiley","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","title":"Universality of random permutations","author":[{"full_name":"He, Xiaoyu","first_name":"Xiaoyu","last_name":"He"},{"full_name":"Kwan, Matthew Alan","last_name":"Kwan","orcid":"0000-0002-4003-7567","first_name":"Matthew Alan","id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3"}],"publication_status":"published","arxiv":1,"abstract":[{"text":"It is a classical fact that for any ε>0, a random permutation of length n=(1+ε)k2/4 typically contains a monotone subsequence of length k. As a far-reaching generalization, Alon conjectured that a random permutation of this same length n is typically k-universal, meaning that it simultaneously contains every pattern of length k. He also made the simple observation that for n=O(k2logk), a random length-n permutation is typically k-universal. We make the first significant progress towards Alon's conjecture by showing that n=2000k2loglogk suffices.","lang":"eng"}],"scopus_import":"1","type":"journal_article","publication_identifier":{"issn":["0024-6093"],"eissn":["1469-2120"]},"extern":"1","citation":{"mla":"He, Xiaoyu, and Matthew Alan Kwan. “Universality of Random Permutations.” Bulletin of the London Mathematical Society, vol. 52, no. 3, Wiley, 2020, pp. 515–29, doi:10.1112/blms.12345.","apa":"He, X., & Kwan, M. A. (2020). Universality of random permutations. Bulletin of the London Mathematical Society. Wiley. https://doi.org/10.1112/blms.12345","chicago":"He, Xiaoyu, and Matthew Alan Kwan. “Universality of Random Permutations.” Bulletin of the London Mathematical Society. Wiley, 2020. https://doi.org/10.1112/blms.12345.","short":"X. He, M.A. Kwan, Bulletin of the London Mathematical Society 52 (2020) 515–529.","ista":"He X, Kwan MA. 2020. Universality of random permutations. Bulletin of the London Mathematical Society. 52(3), 515–529.","ieee":"X. He and M. A. Kwan, “Universality of random permutations,” Bulletin of the London Mathematical Society, vol. 52, no. 3. Wiley, pp. 515–529, 2020.","ama":"He X, Kwan MA. Universality of random permutations. Bulletin of the London Mathematical Society. 2020;52(3):515-529. doi:10.1112/blms.12345"},"quality_controlled":"1","_id":"9573","external_id":{"arxiv":["1911.12878"]},"page":"515-529","year":"2020","date_published":"2020-06-01T00:00:00Z","month":"06","intvolume":" 52","oa":1,"issue":"3","date_updated":"2023-02-23T14:01:23Z","publication":"Bulletin of the London Mathematical Society","doi":"10.1112/blms.12345","main_file_link":[{"url":"https://arxiv.org/abs/1911.12878","open_access":"1"}],"oa_version":"Preprint","volume":52,"day":"01","status":"public","date_created":"2021-06-21T06:23:42Z"},{"publication":"International Mathematics Research Notices","doi":"10.1093/imrn/rnaa004","main_file_link":[{"url":"http://arxiv-export-lb.library.cornell.edu/abs/1810.07462","open_access":"1"}],"oa_version":"Preprint","volume":2020,"date_created":"2021-06-21T08:12:30Z","day":"01","status":"public","page":"8007-8026","external_id":{"arxiv":["1810.07462"]},"year":"2020","date_published":"2020-11-01T00:00:00Z","month":"11","intvolume":" 2020","date_updated":"2023-02-23T14:01:30Z","oa":1,"issue":"21","publication_status":"published","publication_identifier":{"eissn":["1687-0247"],"issn":["1073-7928"]},"extern":"1","citation":{"apa":"Bucić, M., Kwan, M. A., Pokrovskiy, A., & Sudakov, B. (2020). Halfway to Rota’s basis conjecture. International Mathematics Research Notices. Oxford University Press. https://doi.org/10.1093/imrn/rnaa004","mla":"Bucić, Matija, et al. “Halfway to Rota’s Basis Conjecture.” International Mathematics Research Notices, vol. 2020, no. 21, Oxford University Press, 2020, pp. 8007–26, doi:10.1093/imrn/rnaa004.","short":"M. Bucić, M.A. Kwan, A. Pokrovskiy, B. Sudakov, International Mathematics Research Notices 2020 (2020) 8007–8026.","ieee":"M. Bucić, M. A. Kwan, A. Pokrovskiy, and B. Sudakov, “Halfway to Rota’s basis conjecture,” International Mathematics Research Notices, vol. 2020, no. 21. Oxford University Press, pp. 8007–8026, 2020.","ista":"Bucić M, Kwan MA, Pokrovskiy A, Sudakov B. 2020. Halfway to Rota’s basis conjecture. International Mathematics Research Notices. 2020(21), 8007–8026.","ama":"Bucić M, Kwan MA, Pokrovskiy A, Sudakov B. Halfway to Rota’s basis conjecture. International Mathematics Research Notices. 2020;2020(21):8007-8026. doi:10.1093/imrn/rnaa004","chicago":"Bucić, Matija, Matthew Alan Kwan, Alexey Pokrovskiy, and Benny Sudakov. “Halfway to Rota’s Basis Conjecture.” International Mathematics Research Notices. Oxford University Press, 2020. https://doi.org/10.1093/imrn/rnaa004."},"arxiv":1,"scopus_import":"1","abstract":[{"text":"In 1989, Rota made the following conjecture. Given n bases B1,…,Bn in an n-dimensional vector space V⁠, one can always find n disjoint bases of V⁠, each containing exactly one element from each Bi (we call such bases transversal bases). Rota’s basis conjecture remains wide open despite its apparent simplicity and the efforts of many researchers (e.g., the conjecture was recently the subject of the collaborative “Polymath” project). In this paper we prove that one can always find (1/2−o(1))n disjoint transversal bases, improving on the previous best bound of Ω(n/logn)⁠. Our results also apply to the more general setting of matroids.","lang":"eng"}],"type":"journal_article","_id":"9576","quality_controlled":"1","article_processing_charge":"No","language":[{"iso":"eng"}],"article_type":"original","publisher":"Oxford University Press","author":[{"full_name":"Bucić, Matija","last_name":"Bucić","first_name":"Matija"},{"orcid":"0000-0002-4003-7567","last_name":"Kwan","first_name":"Matthew Alan","id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","full_name":"Kwan, Matthew Alan"},{"full_name":"Pokrovskiy, Alexey","first_name":"Alexey","last_name":"Pokrovskiy"},{"full_name":"Sudakov, Benny","first_name":"Benny","last_name":"Sudakov"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","title":"Halfway to Rota’s basis conjecture"},{"type":"journal_article","scopus_import":"1","arxiv":1,"abstract":[{"text":"An n-vertex graph is called C-Ramsey if it has no clique or independent set of size Clogn⁠. All known constructions of Ramsey graphs involve randomness in an essential way, and there is an ongoing line of research towards showing that in fact all Ramsey graphs must obey certain “richness” properties characteristic of random graphs. Motivated by an old problem of Erd̋s and McKay, recently Narayanan, Sahasrabudhe, and Tomon conjectured that for any fixed C, every n-vertex C-Ramsey graph induces subgraphs of Θ(n2) different sizes. In this paper we prove this conjecture.","lang":"eng"}],"publication_identifier":{"issn":["1073-7928"],"eissn":["1687-0247"]},"citation":{"mla":"Kwan, Matthew Alan, and Benny Sudakov. “Ramsey Graphs Induce Subgraphs of Quadratically Many Sizes.” International Mathematics Research Notices, vol. 2020, no. 6, Oxford University Press, 2020, pp. 1621–1638, doi:10.1093/imrn/rny064.","apa":"Kwan, M. A., & Sudakov, B. (2020). Ramsey graphs induce subgraphs of quadratically many sizes. International Mathematics Research Notices. Oxford University Press. https://doi.org/10.1093/imrn/rny064","chicago":"Kwan, Matthew Alan, and Benny Sudakov. “Ramsey Graphs Induce Subgraphs of Quadratically Many Sizes.” International Mathematics Research Notices. Oxford University Press, 2020. https://doi.org/10.1093/imrn/rny064.","ieee":"M. A. Kwan and B. Sudakov, “Ramsey graphs induce subgraphs of quadratically many sizes,” International Mathematics Research Notices, vol. 2020, no. 6. Oxford University Press, pp. 1621–1638, 2020.","short":"M.A. Kwan, B. Sudakov, International Mathematics Research Notices 2020 (2020) 1621–1638.","ista":"Kwan MA, Sudakov B. 2020. Ramsey graphs induce subgraphs of quadratically many sizes. International Mathematics Research Notices. 2020(6), 1621–1638.","ama":"Kwan MA, Sudakov B. Ramsey graphs induce subgraphs of quadratically many sizes. International Mathematics Research Notices. 2020;2020(6):1621–1638. doi:10.1093/imrn/rny064"},"extern":"1","quality_controlled":"1","_id":"9577","publication_status":"published","publisher":"Oxford University Press","title":"Ramsey graphs induce subgraphs of quadratically many sizes","author":[{"id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","first_name":"Matthew Alan","orcid":"0000-0002-4003-7567","last_name":"Kwan","full_name":"Kwan, Matthew Alan"},{"full_name":"Sudakov, Benny","first_name":"Benny","last_name":"Sudakov"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","article_processing_charge":"No","article_type":"original","language":[{"iso":"eng"}],"volume":2020,"day":"01","status":"public","date_created":"2021-06-21T08:30:12Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1093/imrn/rny064"}],"doi":"10.1093/imrn/rny064","publication":"International Mathematics Research Notices","oa_version":"Published Version","month":"03","intvolume":" 2020","date_published":"2020-03-01T00:00:00Z","issue":"6","oa":1,"date_updated":"2023-02-23T14:01:33Z","external_id":{"arxiv":["1711.02937"]},"page":"1621–1638","year":"2020"},{"author":[{"full_name":"Bucić, Matija","last_name":"Bucić","first_name":"Matija"},{"full_name":"Kwan, Matthew Alan","last_name":"Kwan","orcid":"0000-0002-4003-7567","id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","first_name":"Matthew Alan"},{"full_name":"Pokrovskiy, Alexey","first_name":"Alexey","last_name":"Pokrovskiy"},{"full_name":"Sudakov, Benny","last_name":"Sudakov","first_name":"Benny"},{"full_name":"Tran, Tuan","first_name":"Tuan","last_name":"Tran"},{"full_name":"Wagner, Adam Zsolt","first_name":"Adam Zsolt","last_name":"Wagner"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","title":"Nearly-linear monotone paths in edge-ordered graphs","publisher":"Springer","language":[{"iso":"eng"}],"article_type":"original","article_processing_charge":"No","_id":"9578","quality_controlled":"1","extern":"1","publication_identifier":{"issn":["0021-2172"],"eissn":["1565-8511"]},"citation":{"chicago":"Bucić, Matija, Matthew Alan Kwan, Alexey Pokrovskiy, Benny Sudakov, Tuan Tran, and Adam Zsolt Wagner. “Nearly-Linear Monotone Paths in Edge-Ordered Graphs.” Israel Journal of Mathematics. Springer, 2020. https://doi.org/10.1007/s11856-020-2035-7.","ama":"Bucić M, Kwan MA, Pokrovskiy A, Sudakov B, Tran T, Wagner AZ. Nearly-linear monotone paths in edge-ordered graphs. Israel Journal of Mathematics. 2020;238(2):663-685. doi:10.1007/s11856-020-2035-7","ieee":"M. Bucić, M. A. Kwan, A. Pokrovskiy, B. Sudakov, T. Tran, and A. Z. Wagner, “Nearly-linear monotone paths in edge-ordered graphs,” Israel Journal of Mathematics, vol. 238, no. 2. Springer, pp. 663–685, 2020.","short":"M. Bucić, M.A. Kwan, A. Pokrovskiy, B. Sudakov, T. Tran, A.Z. Wagner, Israel Journal of Mathematics 238 (2020) 663–685.","ista":"Bucić M, Kwan MA, Pokrovskiy A, Sudakov B, Tran T, Wagner AZ. 2020. Nearly-linear monotone paths in edge-ordered graphs. Israel Journal of Mathematics. 238(2), 663–685.","mla":"Bucić, Matija, et al. “Nearly-Linear Monotone Paths in Edge-Ordered Graphs.” Israel Journal of Mathematics, vol. 238, no. 2, Springer, 2020, pp. 663–85, doi:10.1007/s11856-020-2035-7.","apa":"Bucić, M., Kwan, M. A., Pokrovskiy, A., Sudakov, B., Tran, T., & Wagner, A. Z. (2020). Nearly-linear monotone paths in edge-ordered graphs. Israel Journal of Mathematics. Springer. https://doi.org/10.1007/s11856-020-2035-7"},"type":"journal_article","scopus_import":"1","abstract":[{"lang":"eng","text":"How long a monotone path can one always find in any edge-ordering of the complete graph Kn? This appealing question was first asked by Chvátal and Komlós in 1971, and has since attracted the attention of many researchers, inspiring a variety of related problems. The prevailing conjecture is that one can always find a monotone path of linear length, but until now the best known lower bound was n2/3-o(1). In this paper we almost close this gap, proving that any edge-ordering of the complete graph contains a monotone path of length n1-o(1)."}],"arxiv":1,"publication_status":"published","date_updated":"2023-02-23T14:01:35Z","issue":"2","oa":1,"intvolume":" 238","month":"07","date_published":"2020-07-01T00:00:00Z","year":"2020","page":"663-685","external_id":{"arxiv":["1809.01468"]},"date_created":"2021-06-21T13:24:35Z","day":"01","status":"public","volume":238,"oa_version":"Preprint","doi":"10.1007/s11856-020-2035-7","main_file_link":[{"url":"https://arxiv.org/abs/1809.01468","open_access":"1"}],"publication":"Israel Journal of Mathematics"},{"article_processing_charge":"No","language":[{"iso":"eng"}],"article_type":"original","publisher":"Wiley","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"full_name":"Kwan, Matthew Alan","first_name":"Matthew Alan","id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","orcid":"0000-0002-4003-7567","last_name":"Kwan"}],"title":"Almost all Steiner triple systems have perfect matchings","publication_status":"published","publication_identifier":{"issn":["0024-6115"],"eissn":["1460-244X"]},"extern":"1","citation":{"apa":"Kwan, M. A. (2020). Almost all Steiner triple systems have perfect matchings. Proceedings of the London Mathematical Society. Wiley. https://doi.org/10.1112/plms.12373","mla":"Kwan, Matthew Alan. “Almost All Steiner Triple Systems Have Perfect Matchings.” Proceedings of the London Mathematical Society, vol. 121, no. 6, Wiley, 2020, pp. 1468–95, doi:10.1112/plms.12373.","ista":"Kwan MA. 2020. Almost all Steiner triple systems have perfect matchings. Proceedings of the London Mathematical Society. 121(6), 1468–1495.","ieee":"M. A. Kwan, “Almost all Steiner triple systems have perfect matchings,” Proceedings of the London Mathematical Society, vol. 121, no. 6. Wiley, pp. 1468–1495, 2020.","short":"M.A. Kwan, Proceedings of the London Mathematical Society 121 (2020) 1468–1495.","ama":"Kwan MA. Almost all Steiner triple systems have perfect matchings. Proceedings of the London Mathematical Society. 2020;121(6):1468-1495. doi:10.1112/plms.12373","chicago":"Kwan, Matthew Alan. “Almost All Steiner Triple Systems Have Perfect Matchings.” Proceedings of the London Mathematical Society. Wiley, 2020. https://doi.org/10.1112/plms.12373."},"type":"journal_article","abstract":[{"text":"We show that for any 𝑛 divisible by 3, almost all order- 𝑛 Steiner triple systems have a perfect matching (also known as a parallel class or resolution class). In fact, we prove a general upper bound on the number of perfect matchings in a Steiner triple system and show that almost all Steiner triple systems essentially attain this maximum. We accomplish this via a general theorem comparing a uniformly random Steiner triple system to the outcome of the triangle removal process, which we hope will be useful for other problems. Our methods can also be adapted to other types of designs; for example, we sketch a proof of the theorem that almost all Latin squares have transversals.","lang":"eng"}],"scopus_import":"1","arxiv":1,"_id":"9581","quality_controlled":"1","page":"1468-1495","external_id":{"arxiv":["1611.02246"]},"year":"2020","month":"12","intvolume":" 121","date_published":"2020-12-01T00:00:00Z","date_updated":"2023-02-23T14:01:43Z","issue":"6","oa":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1611.02246"}],"doi":"10.1112/plms.12373","publication":"Proceedings of the London Mathematical Society","oa_version":"Preprint","volume":121,"date_created":"2021-06-22T06:35:16Z","day":"01","status":"public"},{"volume":40,"date_created":"2021-06-22T06:42:26Z","day":"01","status":"public","doi":"10.1007/s00493-019-4086-0","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1810.12144"}],"publication":"Combinatorica","oa_version":"Preprint","intvolume":" 40","month":"04","date_published":"2020-04-01T00:00:00Z","date_updated":"2023-02-23T14:01:45Z","issue":"2","oa":1,"page":"283-305","external_id":{"arxiv":["1810.12144"]},"year":"2020","publication_identifier":{"eissn":["1439-6912"],"issn":["0209-9683"]},"extern":"1","citation":{"apa":"Kwan, M. A., Letzter, S., Sudakov, B., & Tran, T. (2020). Dense induced bipartite subgraphs in triangle-free graphs. Combinatorica. Springer. https://doi.org/10.1007/s00493-019-4086-0","mla":"Kwan, Matthew Alan, et al. “Dense Induced Bipartite Subgraphs in Triangle-Free Graphs.” Combinatorica, vol. 40, no. 2, Springer, 2020, pp. 283–305, doi:10.1007/s00493-019-4086-0.","ama":"Kwan MA, Letzter S, Sudakov B, Tran T. Dense induced bipartite subgraphs in triangle-free graphs. Combinatorica. 2020;40(2):283-305. doi:10.1007/s00493-019-4086-0","ista":"Kwan MA, Letzter S, Sudakov B, Tran T. 2020. Dense induced bipartite subgraphs in triangle-free graphs. Combinatorica. 40(2), 283–305.","short":"M.A. Kwan, S. Letzter, B. Sudakov, T. Tran, Combinatorica 40 (2020) 283–305.","ieee":"M. A. Kwan, S. Letzter, B. Sudakov, and T. Tran, “Dense induced bipartite subgraphs in triangle-free graphs,” Combinatorica, vol. 40, no. 2. Springer, pp. 283–305, 2020.","chicago":"Kwan, Matthew Alan, Shoham Letzter, Benny Sudakov, and Tuan Tran. “Dense Induced Bipartite Subgraphs in Triangle-Free Graphs.” Combinatorica. Springer, 2020. https://doi.org/10.1007/s00493-019-4086-0."},"type":"journal_article","arxiv":1,"scopus_import":"1","abstract":[{"text":"The problem of finding dense induced bipartite subgraphs in H-free graphs has a long history, and was posed 30 years ago by Erdős, Faudree, Pach and Spencer. In this paper, we obtain several results in this direction. First we prove that any H-free graph with minimum degree at least d contains an induced bipartite subgraph of minimum degree at least cH log d/log log d, thus nearly confirming one and proving another conjecture of Esperet, Kang and Thomassé. Complementing this result, we further obtain optimal bounds for this problem in the case of dense triangle-free graphs, and we also answer a question of Erdœs, Janson, Łuczak and Spencer.","lang":"eng"}],"_id":"9582","quality_controlled":"1","publication_status":"published","publisher":"Springer","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"full_name":"Kwan, Matthew Alan","first_name":"Matthew Alan","id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","orcid":"0000-0002-4003-7567","last_name":"Kwan"},{"full_name":"Letzter, Shoham","first_name":"Shoham","last_name":"Letzter"},{"full_name":"Sudakov, Benny","first_name":"Benny","last_name":"Sudakov"},{"first_name":"Tuan","last_name":"Tran","full_name":"Tran, Tuan"}],"title":"Dense induced bipartite subgraphs in triangle-free graphs","article_processing_charge":"No","language":[{"iso":"eng"}],"article_type":"original"},{"oa":1,"date_updated":"2023-02-23T14:01:48Z","article_number":"e39","date_published":"2020-11-03T00:00:00Z","intvolume":" 8","month":"11","year":"2020","license":"https://creativecommons.org/licenses/by/4.0/","external_id":{"pmid":["1907.06744"]},"status":"public","day":"03","tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"date_created":"2021-06-22T09:12:23Z","ddc":["510"],"volume":8,"pmid":1,"oa_version":"Published Version","publication":"Forum of Mathematics","doi":"10.1017/fms.2020.29","author":[{"first_name":"Asaf","last_name":"Ferber","full_name":"Ferber, Asaf"},{"id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","first_name":"Matthew Alan","orcid":"0000-0002-4003-7567","last_name":"Kwan","full_name":"Kwan, Matthew Alan"}],"title":"Almost all Steiner triple systems are almost resolvable","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","file":[{"file_id":"9584","content_type":"application/pdf","creator":"asandaue","file_size":601516,"access_level":"open_access","checksum":"5553c596bb4db0f38226a56bee9c87a1","relation":"main_file","success":1,"file_name":"2020_CambridgeUniversityPress_Ferber.pdf","date_created":"2021-06-22T09:23:59Z","date_updated":"2021-06-22T09:23:59Z"}],"publisher":"Cambridge University Press","has_accepted_license":"1","article_type":"original","language":[{"iso":"eng"}],"article_processing_charge":"No","quality_controlled":"1","_id":"9583","abstract":[{"lang":"eng","text":"We show that for any n divisible by 3, almost all order-n Steiner triple systems admit a decomposition of almost all their triples into disjoint perfect matchings (that is, almost all Steiner triple systems are almost resolvable)."}],"scopus_import":"1","file_date_updated":"2021-06-22T09:23:59Z","type":"journal_article","citation":{"apa":"Ferber, A., & Kwan, M. A. (2020). Almost all Steiner triple systems are almost resolvable. Forum of Mathematics. Cambridge University Press. https://doi.org/10.1017/fms.2020.29","mla":"Ferber, Asaf, and Matthew Alan Kwan. “Almost All Steiner Triple Systems Are Almost Resolvable.” Forum of Mathematics, vol. 8, e39, Cambridge University Press, 2020, doi:10.1017/fms.2020.29.","ieee":"A. Ferber and M. A. Kwan, “Almost all Steiner triple systems are almost resolvable,” Forum of Mathematics, vol. 8. Cambridge University Press, 2020.","short":"A. Ferber, M.A. Kwan, Forum of Mathematics 8 (2020).","ista":"Ferber A, Kwan MA. 2020. Almost all Steiner triple systems are almost resolvable. Forum of Mathematics. 8, e39.","ama":"Ferber A, Kwan MA. Almost all Steiner triple systems are almost resolvable. Forum of Mathematics. 2020;8. doi:10.1017/fms.2020.29","chicago":"Ferber, Asaf, and Matthew Alan Kwan. “Almost All Steiner Triple Systems Are Almost Resolvable.” Forum of Mathematics. Cambridge University Press, 2020. https://doi.org/10.1017/fms.2020.29."},"publication_identifier":{"eissn":["2050-5094"]},"extern":"1","publication_status":"published"},{"volume":11,"tmp":{"short":"CC BY (3.0)","name":"Creative Commons Attribution 3.0 Unported (CC BY 3.0)","legal_code_url":"https://creativecommons.org/licenses/by/3.0/legalcode","image":"/images/cc_by.png"},"date_created":"2021-07-04T22:01:26Z","ddc":["510","000"],"status":"public","day":"14","doi":"10.20382/jocg.v11i2a7","publication":"Journal of Computational Geometry","oa_version":"Published Version","month":"12","intvolume":" 11","date_published":"2020-12-14T00:00:00Z","acknowledgement":"This research is partially supported by the Office of Naval Research, through grant no. N62909-18-1-2038, and the DFG Collaborative Research Center TRR 109, ‘Discretization in Geometry and Dynamics’, through grant no. I02979-N35 of the Austrian Science Fund (FWF).","date_updated":"2021-08-11T12:26:34Z","issue":"2","oa":1,"page":"162-182","license":"https://creativecommons.org/licenses/by/3.0/","year":"2020","publication_identifier":{"eissn":["1920180X"]},"citation":{"ieee":"H. Edelsbrunner, Z. Virk, and H. Wagner, “Topological data analysis in information space,” Journal of Computational Geometry, vol. 11, no. 2. Carleton University, pp. 162–182, 2020.","ista":"Edelsbrunner H, Virk Z, Wagner H. 2020. Topological data analysis in information space. Journal of Computational Geometry. 11(2), 162–182.","short":"H. Edelsbrunner, Z. Virk, H. Wagner, Journal of Computational Geometry 11 (2020) 162–182.","ama":"Edelsbrunner H, Virk Z, Wagner H. Topological data analysis in information space. Journal of Computational Geometry. 2020;11(2):162-182. doi:10.20382/jocg.v11i2a7","chicago":"Edelsbrunner, Herbert, Ziga Virk, and Hubert Wagner. “Topological Data Analysis in Information Space.” Journal of Computational Geometry. Carleton University, 2020. https://doi.org/10.20382/jocg.v11i2a7.","apa":"Edelsbrunner, H., Virk, Z., & Wagner, H. (2020). Topological data analysis in information space. Journal of Computational Geometry. Carleton University. https://doi.org/10.20382/jocg.v11i2a7","mla":"Edelsbrunner, Herbert, et al. “Topological Data Analysis in Information Space.” Journal of Computational Geometry, vol. 11, no. 2, Carleton University, 2020, pp. 162–82, doi:10.20382/jocg.v11i2a7."},"file_date_updated":"2021-08-11T11:55:11Z","type":"journal_article","scopus_import":"1","abstract":[{"lang":"eng","text":"Various kinds of data are routinely represented as discrete probability distributions. Examples include text documents summarized by histograms of word occurrences and images represented as histograms of oriented gradients. Viewing a discrete probability distribution as a point in the standard simplex of the appropriate dimension, we can understand collections of such objects in geometric and topological terms. Importantly, instead of using the standard Euclidean distance, we look into dissimilarity measures with information-theoretic justification, and we develop the theory needed for applying topological data analysis in this setting. In doing so, we emphasize constructions that enable the usage of existing computational topology software in this context."}],"_id":"9630","quality_controlled":"1","project":[{"_id":"0aa4bc98-070f-11eb-9043-e6fff9c6a316","name":"Discretization in Geometry and Dynamics","grant_number":"I4887"}],"publication_status":"published","has_accepted_license":"1","publisher":"Carleton University","file":[{"date_updated":"2021-08-11T11:55:11Z","date_created":"2021-08-11T11:55:11Z","success":1,"file_name":"2020_JournalOfComputationalGeometry_Edelsbrunner.pdf","checksum":"f02d0b2b3838e7891a6c417fc34ffdcd","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_id":"9882","creator":"asandaue","file_size":1449234}],"title":"Topological data analysis in information space","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"first_name":"Herbert","id":"3FB178DA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-9823-6833","last_name":"Edelsbrunner","full_name":"Edelsbrunner, Herbert"},{"last_name":"Virk","first_name":"Ziga","id":"2E36B656-F248-11E8-B48F-1D18A9856A87","full_name":"Virk, Ziga"},{"first_name":"Hubert","id":"379CA8B8-F248-11E8-B48F-1D18A9856A87","last_name":"Wagner","full_name":"Wagner, Hubert"}],"article_processing_charge":"Yes","department":[{"_id":"HeEd"}],"language":[{"iso":"eng"}],"article_type":"original"},{"year":"2020","conference":{"name":"NeurIPS: Conference on Neural Information Processing Systems","start_date":"2020-12-06","end_date":"2020-12-12","location":"Vancouver, Canada"},"external_id":{"arxiv":["2002.11505"]},"page":"22361-22372","oa":1,"date_updated":"2023-02-23T14:03:03Z","acknowledgement":"We thank Marco Mondelli for discussions related to LDPC decoding, and Giorgi Nadiradze for discussions on analysis of relaxed schedulers. This project has received funding from the European Research Council (ERC) under the European\r\nUnion’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML).","date_published":"2020-12-06T00:00:00Z","month":"12","intvolume":" 33","oa_version":"Published Version","ec_funded":1,"publication":"Advances in Neural Information Processing Systems","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2020/hash/fdb2c3bab9d0701c4a050a4d8d782c7f-Abstract.html","open_access":"1"}],"status":"public","day":"06","date_created":"2021-07-04T22:01:26Z","volume":33,"language":[{"iso":"eng"}],"department":[{"_id":"DaAl"}],"article_processing_charge":"No","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"full_name":"Aksenov, Vitaly","last_name":"Aksenov","first_name":"Vitaly"},{"full_name":"Alistarh, Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","last_name":"Alistarh"},{"last_name":"Korhonen","first_name":"Janne","id":"C5402D42-15BC-11E9-A202-CA2BE6697425","full_name":"Korhonen, Janne"}],"title":"Scalable belief propagation via relaxed scheduling","publisher":"Curran Associates","publication_status":"published","project":[{"call_identifier":"H2020","grant_number":"805223","_id":"268A44D6-B435-11E9-9278-68D0E5697425","name":"Elastic Coordination for Scalable Machine Learning"}],"quality_controlled":"1","_id":"9631","scopus_import":"1","arxiv":1,"abstract":[{"text":"The ability to leverage large-scale hardware parallelism has been one of the key enablers of the accelerated recent progress in machine learning. Consequently, there has been considerable effort invested into developing efficient parallel variants of classic machine learning algorithms. However, despite the wealth of knowledge on parallelization, some classic machine learning algorithms often prove hard to parallelize efficiently while maintaining convergence. In this paper, we focus on efficient parallel algorithms for the key machine learning task of inference on graphical models, in particular on the fundamental belief propagation algorithm. We address the challenge of efficiently parallelizing this classic paradigm by showing how to leverage scalable relaxed schedulers in this context. We present an extensive empirical study, showing that our approach outperforms previous parallel belief propagation implementations both in terms of scalability and in terms of wall-clock convergence time, on a range of practical applications.","lang":"eng"}],"type":"conference","citation":{"chicago":"Aksenov, Vitaly, Dan-Adrian Alistarh, and Janne Korhonen. “Scalable Belief Propagation via Relaxed Scheduling.” In Advances in Neural Information Processing Systems, 33:22361–72. Curran Associates, 2020.","ama":"Aksenov V, Alistarh D-A, Korhonen J. Scalable belief propagation via relaxed scheduling. In: Advances in Neural Information Processing Systems. Vol 33. Curran Associates; 2020:22361-22372.","ieee":"V. Aksenov, D.-A. Alistarh, and J. Korhonen, “Scalable belief propagation via relaxed scheduling,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 22361–22372.","short":"V. Aksenov, D.-A. Alistarh, J. Korhonen, in:, Advances in Neural Information Processing Systems, Curran Associates, 2020, pp. 22361–22372.","ista":"Aksenov V, Alistarh D-A, Korhonen J. 2020. Scalable belief propagation via relaxed scheduling. Advances in Neural Information Processing Systems. NeurIPS: Conference on Neural Information Processing Systems vol. 33, 22361–22372.","mla":"Aksenov, Vitaly, et al. “Scalable Belief Propagation via Relaxed Scheduling.” Advances in Neural Information Processing Systems, vol. 33, Curran Associates, 2020, pp. 22361–72.","apa":"Aksenov, V., Alistarh, D.-A., & Korhonen, J. (2020). Scalable belief propagation via relaxed scheduling. In Advances in Neural Information Processing Systems (Vol. 33, pp. 22361–22372). Vancouver, Canada: Curran Associates."},"publication_identifier":{"isbn":["9781713829546"],"issn":["10495258"]}},{"conference":{"location":"Vancouver, Canada","start_date":"2020-12-06","end_date":"2020-12-12","name":"NeurIPS: Conference on Neural Information Processing Systems"},"page":"18098-18109","external_id":{"arxiv":["2004.14340"]},"year":"2020","acknowledgement":"This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML). Also, we would like to thank Alexander Shevchenko, Alexandra Peste, and other members of the group for fruitful discussions.","intvolume":" 33","month":"12","date_published":"2020-12-06T00:00:00Z","oa":1,"date_updated":"2023-02-23T14:03:06Z","main_file_link":[{"open_access":"1","url":"https://proceedings.neurips.cc/paper/2020/hash/d1ff1ec86b62cd5f3903ff19c3a326b2-Abstract.html"}],"publication":"Advances in Neural Information Processing Systems","ec_funded":1,"oa_version":"Published Version","volume":33,"status":"public","day":"06","date_created":"2021-07-04T22:01:26Z","department":[{"_id":"DaAl"},{"_id":"ToHe"}],"article_processing_charge":"No","language":[{"iso":"eng"}],"publisher":"Curran Associates","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"id":"DD138E24-D89D-11E9-9DC0-DEF6E5697425","first_name":"Sidak Pal","last_name":"Singh","full_name":"Singh, Sidak Pal"},{"orcid":"0000-0003-3650-940X","last_name":"Alistarh","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","first_name":"Dan-Adrian","full_name":"Alistarh, Dan-Adrian"}],"title":"WoodFisher: Efficient second-order approximation for neural network compression","publication_status":"published","project":[{"grant_number":"805223","call_identifier":"H2020","name":"Elastic Coordination for Scalable Machine Learning","_id":"268A44D6-B435-11E9-9278-68D0E5697425"}],"type":"conference","scopus_import":"1","abstract":[{"lang":"eng","text":"Second-order information, in the form of Hessian- or Inverse-Hessian-vector products, is a fundamental tool for solving optimization problems. Recently, there has been significant interest in utilizing this information in the context of deep\r\nneural networks; however, relatively little is known about the quality of existing approximations in this context. Our work examines this question, identifies issues with existing approaches, and proposes a method called WoodFisher to compute a faithful and efficient estimate of the inverse Hessian. Our main application is to neural network compression, where we build on the classic Optimal Brain Damage/Surgeon framework. We demonstrate that WoodFisher significantly outperforms popular state-of-the-art methods for oneshot pruning. Further, even when iterative, gradual pruning is allowed, our method results in a gain in test accuracy over the state-of-the-art approaches, for standard image classification datasets such as ImageNet ILSVRC. We examine how our method can be extended to take into account first-order information, as well as\r\nillustrate its ability to automatically set layer-wise pruning thresholds and perform compression in the limited-data regime. The code is available at the following link, https://github.com/IST-DASLab/WoodFisher."}],"arxiv":1,"citation":{"ama":"Singh SP, Alistarh D-A. WoodFisher: Efficient second-order approximation for neural network compression. In: Advances in Neural Information Processing Systems. Vol 33. Curran Associates; 2020:18098-18109.","ieee":"S. P. Singh and D.-A. Alistarh, “WoodFisher: Efficient second-order approximation for neural network compression,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 18098–18109.","ista":"Singh SP, Alistarh D-A. 2020. WoodFisher: Efficient second-order approximation for neural network compression. Advances in Neural Information Processing Systems. NeurIPS: Conference on Neural Information Processing Systems vol. 33, 18098–18109.","short":"S.P. Singh, D.-A. Alistarh, in:, Advances in Neural Information Processing Systems, Curran Associates, 2020, pp. 18098–18109.","chicago":"Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order Approximation for Neural Network Compression.” In Advances in Neural Information Processing Systems, 33:18098–109. Curran Associates, 2020.","apa":"Singh, S. P., & Alistarh, D.-A. (2020). WoodFisher: Efficient second-order approximation for neural network compression. In Advances in Neural Information Processing Systems (Vol. 33, pp. 18098–18109). Vancouver, Canada: Curran Associates.","mla":"Singh, Sidak Pal, and Dan-Adrian Alistarh. “WoodFisher: Efficient Second-Order Approximation for Neural Network Compression.” Advances in Neural Information Processing Systems, vol. 33, Curran Associates, 2020, pp. 18098–109."},"publication_identifier":{"isbn":["9781713829546"],"issn":["10495258"]},"quality_controlled":"1","_id":"9632"},{"volume":33,"day":"06","status":"public","date_created":"2021-07-04T22:01:27Z","publication":"Advances in Neural Information Processing Systems","main_file_link":[{"url":"https://proceedings.neurips.cc/paper/2020/hash/bdbd5ebfde4934142c8a88e7a3796cd5-Abstract.html","open_access":"1"}],"oa_version":"Published Version","ec_funded":1,"related_material":{"link":[{"url":"https://doi.org/10.1101/2020.10.24.353409","relation":"is_continued_by"}],"record":[{"status":"public","relation":"dissertation_contains","id":"14422"}]},"acknowledgement":"We would like to thank Chaitanya Chintaluri, Georgia Christodoulou, Bill Podlaski and Merima Šabanovic for useful discussions and comments. This work was supported by a Wellcome Trust ´ Senior Research Fellowship (214316/Z/18/Z), a BBSRC grant (BB/N019512/1), an ERC consolidator Grant (SYNAPSEEK), a Leverhulme Trust Project Grant (RPG-2016-446), and funding from École Polytechnique, Paris.","date_published":"2020-12-06T00:00:00Z","month":"12","intvolume":" 33","oa":1,"date_updated":"2023-10-18T09:20:55Z","conference":{"location":"Vancouver, Canada","start_date":"2020-12-06","end_date":"2020-12-12","name":"NeurIPS: Conference on Neural Information Processing Systems"},"page":"16398-16408","year":"2020","scopus_import":"1","abstract":[{"lang":"eng","text":"The search for biologically faithful synaptic plasticity rules has resulted in a large body of models. They are usually inspired by – and fitted to – experimental data, but they rarely produce neural dynamics that serve complex functions. These failures suggest that current plasticity models are still under-constrained by existing data. Here, we present an alternative approach that uses meta-learning to discover plausible synaptic plasticity rules. Instead of experimental data, the rules are constrained by the functions they implement and the structure they are meant to produce. Briefly, we parameterize synaptic plasticity rules by a Volterra expansion and then use supervised learning methods (gradient descent or evolutionary strategies) to minimize a problem-dependent loss function that quantifies how effectively a candidate plasticity rule transforms an initially random network into one with the desired function. We first validate our approach by re-discovering previously described plasticity rules, starting at the single-neuron level and “Oja’s rule”, a simple Hebbian plasticity rule that captures the direction of most variability of inputs to a neuron (i.e., the first principal component). We expand the problem to the network level and ask the framework to find Oja’s rule together with an anti-Hebbian rule such that an initially random two-layer firing-rate network will recover several principal components of the input space after learning. Next, we move to networks of integrate-and-fire neurons with plastic inhibitory afferents. We train for rules that achieve a target firing rate by countering tuned excitation. Our algorithm discovers a specific subset of the manifold of rules that can solve this task. Our work is a proof of principle of an automated and unbiased approach to unveil synaptic plasticity rules that obey biological constraints and can solve complex functions."}],"type":"conference","citation":{"mla":"Confavreux, Basile J., et al. “A Meta-Learning Approach to (Re)Discover Plasticity Rules That Carve a Desired Function into a Neural Network.” Advances in Neural Information Processing Systems, vol. 33, 2020, pp. 16398–408.","apa":"Confavreux, B. J., Zenke, F., Agnes, E. J., Lillicrap, T., & Vogels, T. P. (2020). A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network. In Advances in Neural Information Processing Systems (Vol. 33, pp. 16398–16408). Vancouver, Canada.","chicago":"Confavreux, Basile J, Friedemann Zenke, Everton J. Agnes, Timothy Lillicrap, and Tim P Vogels. “A Meta-Learning Approach to (Re)Discover Plasticity Rules That Carve a Desired Function into a Neural Network.” In Advances in Neural Information Processing Systems, 33:16398–408, 2020.","ama":"Confavreux BJ, Zenke F, Agnes EJ, Lillicrap T, Vogels TP. A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network. In: Advances in Neural Information Processing Systems. Vol 33. ; 2020:16398-16408.","ieee":"B. J. Confavreux, F. Zenke, E. J. Agnes, T. Lillicrap, and T. P. Vogels, “A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2020, vol. 33, pp. 16398–16408.","short":"B.J. Confavreux, F. Zenke, E.J. Agnes, T. Lillicrap, T.P. Vogels, in:, Advances in Neural Information Processing Systems, 2020, pp. 16398–16408.","ista":"Confavreux BJ, Zenke F, Agnes EJ, Lillicrap T, Vogels TP. 2020. A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network. Advances in Neural Information Processing Systems. NeurIPS: Conference on Neural Information Processing Systems vol. 33, 16398–16408."},"publication_identifier":{"issn":["1049-5258"]},"quality_controlled":"1","_id":"9633","publication_status":"published","project":[{"name":"What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent neuronal networks.","_id":"c084a126-5a5b-11eb-8a69-d75314a70a87","grant_number":"214316/Z/18/Z"},{"call_identifier":"H2020","grant_number":"819603","name":"Learning the shape of synaptic plasticity rules for neuronal architectures and function through machine learning.","_id":"0aacfa84-070f-11eb-9043-d7eb2c709234"}],"author":[{"full_name":"Confavreux, Basile J","last_name":"Confavreux","id":"C7610134-B532-11EA-BD9F-F5753DDC885E","first_name":"Basile J"},{"first_name":"Friedemann","last_name":"Zenke","full_name":"Zenke, Friedemann"},{"first_name":"Everton J.","last_name":"Agnes","full_name":"Agnes, Everton J."},{"full_name":"Lillicrap, Timothy","first_name":"Timothy","last_name":"Lillicrap"},{"full_name":"Vogels, Tim P","first_name":"Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","orcid":"0000-0003-3295-6181","last_name":"Vogels"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","title":"A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network","department":[{"_id":"TiVo"}],"article_processing_charge":"No","language":[{"iso":"eng"}]},{"year":"2020","external_id":{"arxiv":["1910.13481"],"pmid":["32007057"]},"date_updated":"2023-02-23T14:03:55Z","oa":1,"issue":"4","date_published":"2020-01-31T00:00:00Z","month":"01","intvolume":" 152","article_number":"044103","oa_version":"Submitted Version","publication":"The Journal of Chemical Physics","doi":"10.1063/1.5134461","main_file_link":[{"open_access":"1","url":"https://pure.qub.ac.uk/en/publications/classical-nucleation-theory-predicts-the-shape-of-the-nucleus-in-homogeneous-solidification(56af848b-eee8-4e9b-93cf-667373e4a49b).html"}],"date_created":"2021-07-15T07:22:24Z","day":"31","status":"public","volume":152,"pmid":1,"language":[{"iso":"eng"}],"article_type":"original","article_processing_charge":"No","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"full_name":"Cheng, Bingqing","first_name":"Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","orcid":"0000-0002-3584-9632","last_name":"Cheng"},{"full_name":"Ceriotti, Michele","first_name":"Michele","last_name":"Ceriotti"},{"full_name":"Tribello, Gareth A.","first_name":"Gareth A.","last_name":"Tribello"}],"title":"Classical nucleation theory predicts the shape of the nucleus in homogeneous solidification","publisher":"AIP Publishing","publication_status":"published","_id":"9658","quality_controlled":"1","citation":{"mla":"Cheng, Bingqing, et al. “Classical Nucleation Theory Predicts the Shape of the Nucleus in Homogeneous Solidification.” The Journal of Chemical Physics, vol. 152, no. 4, 044103, AIP Publishing, 2020, doi:10.1063/1.5134461.","apa":"Cheng, B., Ceriotti, M., & Tribello, G. A. (2020). Classical nucleation theory predicts the shape of the nucleus in homogeneous solidification. The Journal of Chemical Physics. AIP Publishing. https://doi.org/10.1063/1.5134461","chicago":"Cheng, Bingqing, Michele Ceriotti, and Gareth A. Tribello. “Classical Nucleation Theory Predicts the Shape of the Nucleus in Homogeneous Solidification.” The Journal of Chemical Physics. AIP Publishing, 2020. https://doi.org/10.1063/1.5134461.","ieee":"B. Cheng, M. Ceriotti, and G. A. Tribello, “Classical nucleation theory predicts the shape of the nucleus in homogeneous solidification,” The Journal of Chemical Physics, vol. 152, no. 4. AIP Publishing, 2020.","short":"B. Cheng, M. Ceriotti, G.A. Tribello, The Journal of Chemical Physics 152 (2020).","ista":"Cheng B, Ceriotti M, Tribello GA. 2020. Classical nucleation theory predicts the shape of the nucleus in homogeneous solidification. The Journal of Chemical Physics. 152(4), 044103.","ama":"Cheng B, Ceriotti M, Tribello GA. Classical nucleation theory predicts the shape of the nucleus in homogeneous solidification. The Journal of Chemical Physics. 2020;152(4). doi:10.1063/1.5134461"},"publication_identifier":{"issn":["0021-9606"],"eissn":["1089-7690"]},"extern":"1","abstract":[{"lang":"eng","text":"Macroscopic models of nucleation provide powerful tools for understanding activated phase transition processes. These models do not provide atomistic insights and can thus sometimes lack material-specific descriptions. Here, we provide a comprehensive framework for constructing a continuum picture from an atomistic simulation of homogeneous nucleation. We use this framework to determine the equilibrium shape of the solid nucleus that forms inside bulk liquid for a Lennard-Jones potential. From this shape, we then extract the anisotropy of the solid-liquid interfacial free energy, by performing a reverse Wulff construction in the space of spherical harmonic expansions. We find that the shape of the nucleus is nearly spherical and that its anisotropy can be perfectly described using classical models."}],"scopus_import":"1","arxiv":1,"type":"journal_article"},{"status":"public","day":"25","date_created":"2021-07-15T12:15:14Z","pmid":1,"volume":125,"oa_version":"Preprint","doi":"10.1103/physrevlett.125.130602","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2005.07562"}],"publication":"Physical Review Letters","issue":"13","oa":1,"date_updated":"2021-08-09T12:35:58Z","article_number":"130602","intvolume":" 125","month":"09","date_published":"2020-09-25T00:00:00Z","year":"2020","external_id":{"arxiv":["2005.07562"],"pmid":["33034481"]},"quality_controlled":"1","_id":"9664","type":"journal_article","arxiv":1,"scopus_import":"1","abstract":[{"text":"Equilibrium molecular dynamics simulations, in combination with the Green-Kubo (GK) method, have been extensively used to compute the thermal conductivity of liquids. However, the GK method relies on an ambiguous definition of the microscopic heat flux, which depends on how one chooses to distribute energies over atoms. This ambiguity makes it problematic to employ the GK method for systems with nonpairwise interactions. In this work, we show that the hydrodynamic description of thermally driven density fluctuations can be used to obtain the thermal conductivity of a bulk fluid unambiguously, thereby bypassing the need to define the heat flux. We verify that, for a model fluid with only pairwise interactions, our method yields estimates of thermal conductivity consistent with the GK approach. We apply our approach to compute the thermal conductivity of a nonpairwise additive water model at supercritical conditions, and of a liquid hydrogen system described by a machine-learning interatomic potential, at 33 GPa and 2000 K.","lang":"eng"}],"extern":"1","citation":{"chicago":"Cheng, Bingqing, and Daan Frenkel. “Computing the Heat Conductivity of Fluids from Density Fluctuations.” Physical Review Letters. American Physical Society, 2020. https://doi.org/10.1103/physrevlett.125.130602.","ama":"Cheng B, Frenkel D. Computing the heat conductivity of fluids from density fluctuations. Physical Review Letters. 2020;125(13). doi:10.1103/physrevlett.125.130602","ista":"Cheng B, Frenkel D. 2020. Computing the heat conductivity of fluids from density fluctuations. Physical Review Letters. 125(13), 130602.","ieee":"B. Cheng and D. Frenkel, “Computing the heat conductivity of fluids from density fluctuations,” Physical Review Letters, vol. 125, no. 13. American Physical Society, 2020.","short":"B. Cheng, D. Frenkel, Physical Review Letters 125 (2020).","mla":"Cheng, Bingqing, and Daan Frenkel. “Computing the Heat Conductivity of Fluids from Density Fluctuations.” Physical Review Letters, vol. 125, no. 13, 130602, American Physical Society, 2020, doi:10.1103/physrevlett.125.130602.","apa":"Cheng, B., & Frenkel, D. (2020). Computing the heat conductivity of fluids from density fluctuations. Physical Review Letters. American Physical Society. https://doi.org/10.1103/physrevlett.125.130602"},"publication_identifier":{"issn":["0031-9007"],"eissn":["1079-7114"]},"publication_status":"published","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"full_name":"Cheng, Bingqing","first_name":"Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","orcid":"0000-0002-3584-9632","last_name":"Cheng"},{"full_name":"Frenkel, Daan","first_name":"Daan","last_name":"Frenkel"}],"title":"Computing the heat conductivity of fluids from density fluctuations","publisher":"American Physical Society","article_type":"original","language":[{"iso":"eng"}],"article_processing_charge":"No"},{"year":"2020","external_id":{"pmid":["32459228"],"arxiv":["1909.08934"]},"page":"12697-12705","date_updated":"2023-02-23T14:04:16Z","oa":1,"issue":"22","date_published":"2020-06-14T00:00:00Z","intvolume":" 22","month":"06","oa_version":"Published Version","publication":"Physical Chemistry Chemical Physics","doi":"10.1039/d0cp02513e","ddc":["530"],"tmp":{"short":"CC BY (3.0)","name":"Creative Commons Attribution 3.0 Unported (CC BY 3.0)","legal_code_url":"https://creativecommons.org/licenses/by/3.0/legalcode","image":"/images/cc_by.png"},"date_created":"2021-07-15T12:37:27Z","day":"14","status":"public","volume":22,"pmid":1,"language":[{"iso":"eng"}],"article_type":"original","article_processing_charge":"No","title":"Predicting the phase diagram of titanium dioxide with random search and pattern recognition","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"first_name":"Aleks","last_name":"Reinhardt","full_name":"Reinhardt, Aleks"},{"full_name":"Pickard, Chris J.","last_name":"Pickard","first_name":"Chris J."},{"last_name":"Cheng","orcid":"0000-0002-3584-9632","first_name":"Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","full_name":"Cheng, Bingqing"}],"file":[{"date_updated":"2021-07-15T12:43:51Z","date_created":"2021-07-15T12:43:51Z","file_name":"202_PhysicalChemistryChemicalPhysics_Reinhardt.pdf","success":1,"relation":"main_file","access_level":"open_access","checksum":"0a6872972b1b2e60f9095d39b01753fa","file_size":3151206,"creator":"asandaue","file_id":"9667","content_type":"application/pdf"}],"has_accepted_license":"1","publisher":"Royal Society of Chemistry","publication_status":"published","_id":"9666","quality_controlled":"1","citation":{"apa":"Reinhardt, A., Pickard, C. J., & Cheng, B. (2020). Predicting the phase diagram of titanium dioxide with random search and pattern recognition. Physical Chemistry Chemical Physics. Royal Society of Chemistry. https://doi.org/10.1039/d0cp02513e","mla":"Reinhardt, Aleks, et al. “Predicting the Phase Diagram of Titanium Dioxide with Random Search and Pattern Recognition.” Physical Chemistry Chemical Physics, vol. 22, no. 22, Royal Society of Chemistry, 2020, pp. 12697–705, doi:10.1039/d0cp02513e.","ieee":"A. Reinhardt, C. J. Pickard, and B. Cheng, “Predicting the phase diagram of titanium dioxide with random search and pattern recognition,” Physical Chemistry Chemical Physics, vol. 22, no. 22. Royal Society of Chemistry, pp. 12697–12705, 2020.","short":"A. Reinhardt, C.J. Pickard, B. Cheng, Physical Chemistry Chemical Physics 22 (2020) 12697–12705.","ista":"Reinhardt A, Pickard CJ, Cheng B. 2020. Predicting the phase diagram of titanium dioxide with random search and pattern recognition. Physical Chemistry Chemical Physics. 22(22), 12697–12705.","ama":"Reinhardt A, Pickard CJ, Cheng B. Predicting the phase diagram of titanium dioxide with random search and pattern recognition. Physical Chemistry Chemical Physics. 2020;22(22):12697-12705. doi:10.1039/d0cp02513e","chicago":"Reinhardt, Aleks, Chris J. Pickard, and Bingqing Cheng. “Predicting the Phase Diagram of Titanium Dioxide with Random Search and Pattern Recognition.” Physical Chemistry Chemical Physics. Royal Society of Chemistry, 2020. https://doi.org/10.1039/d0cp02513e."},"extern":"1","publication_identifier":{"eissn":["1463-9084"],"issn":["1463-9076"]},"abstract":[{"lang":"eng","text":"Predicting phase stabilities of crystal polymorphs is central to computational materials science and chemistry. Such predictions are challenging because they first require searching for potential energy minima and then performing arduous free-energy calculations to account for entropic effects at finite temperatures. Here, we develop a framework that facilitates such predictions by exploiting all the information obtained from random searches of crystal structures. This framework combines automated clustering, classification and visualisation of crystal structures with machine-learning estimation of their enthalpy and entropy. We demonstrate the framework on the technologically important system of TiO2, which has many polymorphs, without relying on prior knowledge of known phases. We find a number of new phases and predict the phase diagram and metastabilities of crystal polymorphs at 1600 K, benchmarking the results against full free-energy calculations."}],"scopus_import":"1","arxiv":1,"file_date_updated":"2021-07-15T12:43:51Z","type":"journal_article"},{"publisher":"Springer Nature","has_accepted_license":"1","file":[{"date_created":"2021-07-15T14:05:45Z","date_updated":"2021-07-15T14:05:45Z","success":1,"file_name":"2020_NatureCommunications_Monserrat.pdf","access_level":"open_access","relation":"main_file","checksum":"1edd9b6d8fa791f8094d87bd6453955b","file_id":"9672","content_type":"application/pdf","file_size":1385954,"creator":"asandaue"}],"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"last_name":"Monserrat","first_name":"Bartomeu","full_name":"Monserrat, Bartomeu"},{"first_name":"Jan Gerit","last_name":"Brandenburg","full_name":"Brandenburg, Jan Gerit"},{"full_name":"Engel, Edgar A.","last_name":"Engel","first_name":"Edgar A."},{"first_name":"Bingqing","id":"cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9","last_name":"Cheng","orcid":"0000-0002-3584-9632","full_name":"Cheng, Bingqing"}],"title":"Liquid water contains the building blocks of diverse ice phases","article_processing_charge":"No","article_type":"original","language":[{"iso":"eng"}],"type":"journal_article","file_date_updated":"2021-07-15T14:05:45Z","abstract":[{"text":"Water molecules can arrange into a liquid with complex hydrogen-bond networks and at least 17 experimentally confirmed ice phases with enormous structural diversity. It remains a puzzle how or whether this multitude of arrangements in different phases of water are related. Here we investigate the structural similarities between liquid water and a comprehensive set of 54 ice phases in simulations, by directly comparing their local environments using general atomic descriptors, and also by demonstrating that a machine-learning potential trained on liquid water alone can predict the densities, lattice energies, and vibrational properties of the ices. The finding that the local environments characterising the different ice phases are found in water sheds light on the phase behavior of water, and rationalizes the transferability of water models between different phases.","lang":"eng"}],"scopus_import":"1","publication_identifier":{"eissn":["2041-1723"]},"extern":"1","citation":{"mla":"Monserrat, Bartomeu, et al. “Liquid Water Contains the Building Blocks of Diverse Ice Phases.” Nature Communications, vol. 11, no. 1, 5757, Springer Nature, 2020, doi:10.1038/s41467-020-19606-y.","apa":"Monserrat, B., Brandenburg, J. G., Engel, E. A., & Cheng, B. (2020). Liquid water contains the building blocks of diverse ice phases. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-020-19606-y","chicago":"Monserrat, Bartomeu, Jan Gerit Brandenburg, Edgar A. Engel, and Bingqing Cheng. “Liquid Water Contains the Building Blocks of Diverse Ice Phases.” Nature Communications. Springer Nature, 2020. https://doi.org/10.1038/s41467-020-19606-y.","ama":"Monserrat B, Brandenburg JG, Engel EA, Cheng B. Liquid water contains the building blocks of diverse ice phases. Nature Communications. 2020;11(1). doi:10.1038/s41467-020-19606-y","ieee":"B. Monserrat, J. G. Brandenburg, E. A. Engel, and B. Cheng, “Liquid water contains the building blocks of diverse ice phases,” Nature Communications, vol. 11, no. 1. Springer Nature, 2020.","short":"B. Monserrat, J.G. Brandenburg, E.A. Engel, B. Cheng, Nature Communications 11 (2020).","ista":"Monserrat B, Brandenburg JG, Engel EA, Cheng B. 2020. Liquid water contains the building blocks of diverse ice phases. Nature Communications. 11(1), 5757."},"quality_controlled":"1","_id":"9671","publication_status":"published","article_number":"5757","intvolume":" 11","month":"11","date_published":"2020-11-13T00:00:00Z","issue":"1","oa":1,"date_updated":"2023-02-23T14:04:25Z","year":"2020","volume":11,"day":"13","status":"public","tmp":{"image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["530","540"],"date_created":"2021-07-15T14:01:35Z","doi":"10.1038/s41467-020-19606-y","publication":"Nature Communications","oa_version":"Published Version"}]