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ORCIDYulia Rubanova
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2020 – today
- 2024
[c11]William F. Whitney, Tatiana Lopez-Guevara, Tobias Pfaff, Yulia Rubanova, Thomas Kipf, Kim Stachenfeld, Kelsey R. Allen:
Learning 3D Particle-based Simulators from RGB-D Videos. ICLR 2024- [i10]Tatiana Lopez-Guevara, Yulia Rubanova, William F. Whitney, Tobias Pfaff, Kimberly L. Stachenfeld, Kelsey R. Allen:
Scaling Face Interaction Graph Networks to Real World Scenes. CoRR abs/2401.11985 (2024) - [i9]Yulia Rubanova, Tatiana Lopez-Guevara, Kelsey R. Allen, William F. Whitney, Kimberly L. Stachenfeld, Tobias Pfaff:
Learning rigid-body simulators over implicit shapes for large-scale scenes and vision. CoRR abs/2405.14045 (2024) - [i8]Ziyi Wu, Yulia Rubanova, Rishabh Kabra, Drew A. Hudson, Igor Gilitschenski, Yusuf Aytar, Sjoerd van Steenkiste, Kelsey R. Allen, Thomas Kipf:
Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models. CoRR abs/2406.09292 (2024) - 2023
- [c10]Kelsey R. Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William Whitney, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Tobias Pfaff:
Learning rigid dynamics with face interaction graph networks. ICLR 2023 - [i7]William F. Whitney, Tatiana Lopez-Guevara, Tobias Pfaff, Yulia Rubanova, Thomas Kipf, Kimberly L. Stachenfeld, Kelsey R. Allen:
Learning 3D Particle-based Simulators from RGB-D Videos. CoRR abs/2312.05359 (2023) - 2022
- [c9]Kelsey R. Allen, Tatiana Lopez-Guevara, Yulia Rubanova, Kimberly L. Stachenfeld, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Tobias Pfaff:
Graph network simulators can learn discontinuous, rigid contact dynamics. CoRL 2022: 1157-1167 - [c8]Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia:
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond. ICLR 2022 - [c7]Yulia Rubanova, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Peter W. Battaglia:
Constraint-based graph network simulator. ICML 2022: 18844-18870 - [c6]Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Joseph Dudzik, Matko Bosnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Velickovic:
A Generalist Neural Algorithmic Learner. LoG 2022: 2 - [i6]Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Dudzik, Matko Bosnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Velickovic:
A Generalist Neural Algorithmic Learner. CoRR abs/2209.11142 (2022) - [i5]Kelsey R. Allen, Yulia Rubanova, Tatiana Lopez-Guevara, William Whitney, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Tobias Pfaff:
Learning rigid dynamics with face interaction graph networks. CoRR abs/2212.03574 (2022) - 2021
- [i4]Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia:
Very Deep Graph Neural Networks Via Noise Regularisation. CoRR abs/2106.07971 (2021) - [i3]Yulia Rubanova, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Peter W. Battaglia:
Constraint-based graph network simulator. CoRR abs/2112.09161 (2021) - 2020
- [b1]Yulia Rubanova:
Continuous-time Latent-variable Models for Time Series. University of Toronto, Canada, 2020 - [j1]Moritz Gerstung
, Clemency Jolly, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Kaixian Yu, Maxime Tarabichi, Amit G. Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vázquez-García, Kerstin Haase, Lara Jerman, Subhajit Sengupta, Geoff MacIntyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Marek Cmero, Jonas Demeulemeester, Steven E. Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. L. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, Süleyman Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Yuan, Wenyi Wang, Quaid D. Morris, David J. Adams, Peter J. Campbell, Shaolong Cao, Elizabeth L. Christie, Yupeng Cun, Kevin J. Dawson, Ruben M. Drews, Roland Eils, Matthew Fittall, Dale W. Garsed, Gavin Ha, Henry Lee-Six, Iñigo Martincorena, Layla Oesper, Myron Peto, Benjamin J. Raphael, Daniel T. Rosebrock, Adriana Salcedo, Ruian Shi, Seung Jun Shin, Oliver Spiro, Lincoln D. Stein, Shankar Vembu, David A. Wheeler, Tsun-Po Yang, Paul T. Spellman, David C. Wedge, Peter Van Loo:
The evolutionary history of 2,658 cancers. Nat. 578(7793): 122-128 (2020) - [c5]Caitlin F. Harrigan, Yulia Rubanova, Quaid Morris, Alina Selega:
TrackSigFreq: Subclonal Reconstructions Based on Mutation Signatures and Allele Frequencies. PSB 2020: 238-249 - [c4]Kevin Swersky, Yulia Rubanova, David Dohan, Kevin Murphy:
Amortized Bayesian Optimization over Discrete Spaces. UAI 2020: 769-778
2010 – 2019
- 2019
- [c3]Yulia Rubanova, Tian Qi Chen, David Duvenaud:
Latent Ordinary Differential Equations for Irregularly-Sampled Time Series. NeurIPS 2019: 5321-5331 - [i2]Yulia Rubanova, Ricky T. Q. Chen, David Duvenaud:
Latent ODEs for Irregularly-Sampled Time Series. CoRR abs/1907.03907 (2019) - 2018
- [c2]Yulia Rubanova, Ruian Shi, Roujia Li, Jeff Wintersinger, Amit G. Deshwar, Nil Sahin, Quaid Morris:
Reconstructing evolutionary trajectories of mutations in cancer. ICLR (Workshop) 2018 - [c1]Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, David Duvenaud:
Neural Ordinary Differential Equations. NeurIPS 2018: 6572-6583 - [i1]Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, David Duvenaud:
Neural Ordinary Differential Equations. CoRR abs/1806.07366 (2018)
Coauthor Index
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