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ORCIDKelsey R. Allen
Person information
- affiliation: Massachusetts Institute of Technology (MIT), CBMM, Cambridge, MA, USA
- affiliation: University of British Columbia, Department of Computer Science, Vancouver, BC, Canada
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2020 – today
- 2024
[i13]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)- [i12]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) - [i11]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
- [c25]Tony Chen, Kelsey R. Allen, Samuel J. Cheyette, Josh Tenenbaum, Kevin A. Smith:
"Just In Time" Representations for Mental Simulation in Intuitive Physics. CogSci 2023 - [c24]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 - [i10]Marin Vlastelica, Tatiana Lopez-Guevara, Kelsey R. Allen, Peter W. Battaglia, Arnaud Doucet, Kimberly L. Stachenfeld:
Diffusion Generative Inverse Design. CoRR abs/2309.02040 (2023) - [i9]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
- [c23]Haoliang Wang, Kelsey R. Allen, Ed Vul, Judith E. Fan:
Generalizing physical prediction by composing forces and objects. CogSci 2022 - [c22]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 - [c21]Kelsey R. Allen, Tatiana Lopez-Guevara, Kimberly L. Stachenfeld, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Jessica B. Hamrick, Tobias Pfaff:
Inverse Design for Fluid-Structure Interactions using Graph Network Simulators. NeurIPS 2022 - [i8]Kelsey R. Allen, Tatiana Lopez-Guevara, Kimberly L. Stachenfeld, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Jessica B. Hamrick, Tobias Pfaff:
Physical Design using Differentiable Learned Simulators. CoRR abs/2202.00728 (2022) - [i7]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
- [c20]Kelsey R. Allen, Kevin A. Smith, Laura-Ashleigh Bird, Josh Tenenbaum, Tamar R. Makin, Dorothy Cowie:
Meta-strategy learning in physical problem-solving: the effect of embodied experience. CogSci 2021 - [c19]Franziska Brändle, Kelsey R. Allen, Josh Tenenbaum, Eric Schulz:
Using Games to Understand Intelligence. CogSci 2021 - [c18]Zachary Davis, Kelsey R. Allen, Tobias Gerstenberg:
Who went fishing? Inferences from social evaluations. CogSci 2021 - [c17]João Loula, Kelsey R. Allen, Josh Tenenbaum:
Combining rules and simulation to explain infant physical learning. CogSci 2021 - 2020
- [c16]Tom Silver, Kelsey R. Allen, Alex K. Lew, Leslie Pack Kaelbling, Josh Tenenbaum:
Few-Shot Bayesian Imitation Learning with Logical Program Policies. AAAI 2020: 10251-10258 - [c15]Kelsey R. Allen, Kevin Smith, Ulyana Piterbarg, Robert Chen, Josh Tenenbaum:
Abstract strategy learning underlies flexible transfer in physical problem solving. CogSci 2020 - [c14]João Loula, Kelsey R. Allen, Josh Tenenbaum:
A Task and Motion Approach to the Development of Planning. CogSci 2020 - [c13]João Loula, Kelsey R. Allen, Tom Silver, Josh Tenenbaum:
Learning constraint-based planning models from demonstrations. IROS 2020: 5410-5416
2010 – 2019
- 2019
- [c12]Kelsey R. Allen, Kevin A. Smith, Josh Tenenbaum:
Rapid Trial-and-Error Learning in Physical Problem Solving. CogSci 2019: 90 - [c11]João Loula, Tom Silver, Kelsey R. Allen, Josh Tenenbaum:
Discovering a symbolic planning language from continuous experience. CogSci 2019: 2193 - [c10]Victoria Xia, Zi Wang, Kelsey R. Allen, Tom Silver, Leslie Pack Kaelbling:
Learning sparse relational transition models. ICLR (Poster) 2019 - [c9]Kelsey R. Allen, Evan Shelhamer, Hanul Shin, Joshua B. Tenenbaum:
Infinite Mixture Prototypes for Few-shot Learning. ICML 2019: 232-241 - [c8]Marc Toussaint, Kelsey R. Allen, Kevin A. Smith, Joshua B. Tenenbaum:
Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning - Extended Abtract. IJCAI 2019: 6231-6235 - [i6]Kelsey R. Allen, Evan Shelhamer, Hanul Shin, Joshua B. Tenenbaum:
Infinite Mixture Prototypes for Few-Shot Learning. CoRR abs/1902.04552 (2019) - [i5]Tom Silver, Kelsey R. Allen, Alex K. Lew, Leslie Pack Kaelbling, Josh Tenenbaum:
Few-Shot Bayesian Imitation Learning with Logic over Programs. CoRR abs/1904.06317 (2019) - [i4]Kelsey R. Allen, Kevin A. Smith, Joshua B. Tenenbaum:
The Tools Challenge: Rapid Trial-and-Error Learning in Physical Problem Solving. CoRR abs/1907.09620 (2019) - 2018
- [c7]Jessica B. Hamrick, Kelsey R. Allen, Victor Bapst, Tina Zhu, Kevin R. McKee, Josh Tenenbaum, Peter W. Battaglia:
Relational inductive bias for physical construction in humans and machines. CogSci 2018 - [c6]Filipe de Avila Belbute-Peres, Kevin A. Smith, Kelsey R. Allen, Josh Tenenbaum, J. Zico Kolter:
End-to-End Differentiable Physics for Learning and Control. NeurIPS 2018: 7178-7189 - [c5]Marc Toussaint, Kelsey R. Allen, Kevin A. Smith, Joshua B. Tenenbaum:
Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning. Robotics: Science and Systems 2018 - [i3]Jessica B. Hamrick, Kelsey R. Allen, Victor Bapst, Tina Zhu, Kevin R. McKee, Joshua B. Tenenbaum, Peter W. Battaglia:
Relational inductive bias for physical construction in humans and machines. CoRR abs/1806.01203 (2018) - [i2]Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, H. Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew M. Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu:
Relational inductive biases, deep learning, and graph networks. CoRR abs/1806.01261 (2018) - [i1]Tom Silver, Kelsey R. Allen, Josh Tenenbaum, Leslie Pack Kaelbling:
Residual Policy Learning. CoRR abs/1812.06298 (2018) - 2017
- [c4]Kelsey R. Allen, Kevin A. Smith, Josh Tenenbaum:
Simulation and heuristics in flexible tool use. CogSci 2017 - 2016
- [c3]Kelsey R. Allen, Ilker Yildirim, Josh Tenenbaum:
Integrating identification and perception: A case study of familiar and unfamiliar face processing. CogSci 2016 - 2015
- [c2]Kelsey R. Allen, Julian Jara-Ettinger, Tobias Gerstenberg, Max Kleiman-Weiner, Joshua B. Tenenbaum:
Go fishing! Responsibility judgments when cooperation breaks down. CogSci 2015 - 2014
- [c1]Kelsey R. Allen, Giuseppe Carenini, Raymond T. Ng:
Detecting Disagreement in Conversations using Pseudo-Monologic Rhetorical Structure. EMNLP 2014: 1169-1180
Coauthor Index
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