Yulia Rubanova

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 22

Top Topics

Network Simulator

Hypothesis Space

Real World Scenes

Evolutionary History

Top Venues

Publications

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 (2024)
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 (2024)
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)
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 (2024)
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 (2023)
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)
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 (2022)
Yulia Rubanova, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Peter W. Battaglia
Constraint-based graph network simulator. ICML (2022)
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)
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 (2022)
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)
Kelsey R. Allen, Tatiana Lopez-Guevara, Yulia Rubanova, Kimberly Stachenfeld, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Tobias Pfaff
Graph network simulators can learn discontinuous, rigid contact dynamics. CoRL (2022)
Yulia Rubanova, Alvaro Sanchez-Gonzalez, Tobias Pfaff, Peter W. Battaglia
Constraint-based graph network simulator. CoRR (2021)
Jonathan Godwin, Michael Schaarschmidt, Alexander Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia
Very Deep Graph Neural Networks Via Noise Regularisation. CoRR (2021)
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) (2020)
Kevin Swersky, Yulia Rubanova, David Dohan, Kevin Murphy
Amortized Bayesian Optimization over Discrete Spaces. UAI (2020)
Caitlin F. Harrigan, Yulia Rubanova, Quaid Morris, Alina Selega
TrackSigFreq: Subclonal Reconstructions Based on Mutation Signatures and Allele Frequencies. PSB (2020)
Yulia Rubanova, Tian Qi Chen, David Duvenaud
Latent Ordinary Differential Equations for Irregularly-Sampled Time Series. NeurIPS (2019)
Yulia Rubanova, Ricky T. Q. Chen, David Duvenaud
Latent ODEs for Irregularly-Sampled Time Series. CoRR (2019)
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)
Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, David Duvenaud
Neural Ordinary Differential Equations. NeurIPS (2018)
Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, David Duvenaud
Neural Ordinary Differential Equations. CoRR (2018)