| Neural ordinary differential equations RTQ Chen, Y Rubanova, J Bettencourt, DK Duvenaud Advances in neural information processing systems 31, 2018 | 5569 | 2018 |
| Pan-cancer analysis of whole genomes Nature 578 (7793), 82-93, 2020 | 1899* | 2020 |
| The evolutionary history of 2,658 cancers M Gerstung, C Jolly, I Leshchiner, SC Dentro, S Gonzalez, D Rosebrock, ... Nature 578 (7793), 122-128, 2020 | 968 | 2020 |
| Latent ordinary differential equations for irregularly-sampled time series Y Rubanova, RTQ Chen, DK Duvenaud Advances in neural information processing systems 32, 2019 | 928 | 2019 |
| Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ... Cell 184 (8), 2239-2254. e39, 2021 | 348 | 2021 |
| The evolutionary landscape of localized prostate cancers drives clinical aggression SMG Espiritu, LY Liu, Y Rubanova, V Bhandari, EM Holgersen, LM Szyca, ... Cell 173 (4), 1003-1013. e15, 2018 | 244 | 2018 |
| Simple gnn regularisation for 3d molecular property prediction & beyond J Godwin, M Schaarschmidt, A Gaunt, A Sanchez-Gonzalez, Y Rubanova, ... arXiv preprint arXiv:2106.07971, 2021 | 121 | 2021 |
| A generalist neural algorithmic learner B Ibarz, V Kurin, G Papamakarios, K Nikiforou, M Bennani, R Csordás, ... Learning on graphs conference, 2: 1-2: 23, 2022 | 65 | 2022 |
| Neural ordinary differential equations (2018) RTQ Chen, Y Rubanova, J Bettencourt, D Duvenaud arXiv preprint arXiv:1806.07366, 1806 | 59 | 1806 |
| Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig Y Rubanova, R Shi, CF Harrigan, R Li, J Wintersinger, N Sahin, ... Nature communications 11 (1), 731, 2020 | 55* | 2020 |
| Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ... BioRxiv, 312041, 2018 | 50* | 2018 |
| Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples MH Bailey, WU Meyerson, LJ Dursi, LB Wang, G Dong, WW Liang, ... Nature communications 11 (1), 4748, 2020 | 44 | 2020 |
| Amortized bayesian optimization over discrete spaces Y Rubanova, D Dohan, K Swersky, K Murphy Conference on Uncertainty in Artificial Intelligence, 769-778, 2020 | 42* | 2020 |
| Graph network simulators can learn discontinuous, rigid contact dynamics KR Allen, TL Guevara, Y Rubanova, K Stachenfeld, A Sanchez-Gonzalez, ... Conference on Robot Learning, 1157-1167, 2023 | 40 | 2023 |
| Learning rigid dynamics with face interaction graph networks KR Allen, Y Rubanova, T Lopez-Guevara, W Whitney, ... arXiv preprint arXiv:2212.03574, 2022 | 30 | 2022 |
| Constraint-based graph network simulator Y Rubanova, A Sanchez-Gonzalez, T Pfaff, P Battaglia arXiv preprint arXiv:2112.09161, 2021 | 30 | 2021 |
| Very deep graph neural networks via noise regularisation J Godwin, M Schaarschmidt, A Gaunt, A Sanchez-Gonzalez, Y Rubanova, ... arXiv preprint arXiv:2106.07971 2, 2021 | 25 | 2021 |
| TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies CF Harrigan, Y Rubanova, Q Morris, A Selega PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020, 238-249, 2019 | 13 | 2019 |
| Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types. bioRxiv (2018) SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ... URL https://www. biorxiv. org/content/10.1101/312041v4, 0 | 4 | |
| Learning 3D Particle-based Simulators from RGB-D Videos WF Whitney, T Lopez-Guevara, T Pfaff, Y Rubanova, T Kipf, K Stachenfeld, ... arXiv preprint arXiv:2312.05359, 2023 | 3 | 2023 |
David DuvenaudAssociate Professor, University of TorontoVerified email at cs.toronto.edu
