Simulations

Publication

Denoising diffusion samplers

Francisco Vargas, Will Grathwohl, Arnaud Doucet

ICLR

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Distilling Internet-Scale Vision-Language Models into Embodied Agents

Kenneth Marino, Arun Ahuja, Rob Fergus, Ishita Dasgupta, Theodore Sumers *

arXiv

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Learning rigid dynamics with face interaction graph networks

Kelsey Allen, Yulia Rubanova, Tatiana Guevara, Will Whitney, Alvaro Sanchez, Peter Battaglia, Tobias Pfaff

arXiv

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Learning rigid dynamics with face interaction graph networks

Kelsey Allen, Yulia Rubanova, Tatiana Guevara, Will Whitney, Alvaro Sanchez, Peter Battaglia, Tobias Pfaff

arXiv

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Inverse Design for Fluid-Structure Interactions using Graph Network Simulators

Kelsey Allen, Tatiana Guevara, Kimberly Stachenfeld, Alvaro Sanchez, Peter Battaglia, Jessica Hamrick, Tobias Pfaff

NeurIPS

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Semi-analytical Industrial Cooling System Model for Reinforcement Learning

Yuri Chervonyi, Praneet Dutta, Piotr Trochim *, Octavian Voicu, Cosmin Paduraru, Crystal Qian, Emre Karagozler, Jared Quincy Davis, Richard Chippendale *, Gautam Bajaj *, Sims Witherspoon, Jerry Luo

arXiv

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MultiScale MeshGraphNets

Meire Fortunato, Tobias Pfaff, Peter Wirnsberger, Alexander Pritzel, Peter Battaglia

ICML Workshop

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Constraint-based graph network simulator

Yulia Rubanova, Alvaro Sanchez, Tobias Pfaff, Peter Battaglia

ICML

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Which priors matter? Benchmarking models for learning latent dynamics

Alex Botev, Drew Jaegle, Peter Wirnsberger, Daniel Hennes, Irina Higgins

NeurIPS

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Learning Mesh-Based Simulation with Graph Networks

Tobias Pfaff, Meire Fortunato, Alvaro Sanchez-Gonzalez, Peter Battaglia

arXiv

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Lagrangian Neural Networks

Miles Cranmer *, S Greydanus *, S Hoyer *, Peter Battaglia, David Spergel *, Shirley Ho *

arXiv

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Learning to Simulate Complex Physics with Graph Networks

Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying *, Jure Leskovec *, Peter Battaglia

ICML

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Targeted free energy estimation via learned mappings

Peter Wirnsberger, Andy Ballard, George Papamakarios, Stuart Abercrombie, Sébastien Racanière, Alexander Pritzel, Danilo Jimenez Rezende, Charles Blundell

arXiv

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Deep Neuroethology of a Virtual Rodent

Josh Merel, Diego Aldarondo *, Jesse Marshall *, Yuval Tassa, Gregory Wayne, Bence Ölveczky *

arXiv

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Attention Privileged Reinforcement Learning For Domain Transfer

Sasha Salter *, Dushyant Rao, Markus Wulfmeier, Raia Hadsell, Ingmar Posner *

arXiv

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Hamiltonian Graph Networks with ODE Integrators

Alvaro Sanchez-Gonzalez, Victor Bapst, K Cranmer *, Peter Battaglia

arXiv

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Learning Symbolic Physics with Graph Networks

Miles Cranmer *, Rui Xu *, Peter Battaglia, Shirley Ho *

NeurIPS

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Publication

Sim2real transfer learning for 3D pose estimation: motion to the rescue

Carl Doersch, Andrew Zisserman

arXiv

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Robust Reinforcement Learning for Continuous Control with Model Misspecification

Daniel Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy Mann, Todd Hester, Martin Riedmiller

arXiv

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Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks

Stephen James *, Paul Wohlhart *, Mrinal Kalakrishnan *, Dmitry Kalashnikov *, Alex Irpan *, Julian Ibarz *, Sergey Levine *, Raia Hadsell, Konstantinos Bousmalis

arXiv

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Modeling human intuitions about liquid flow with particle-based simulation

C J Bates *, I Yildirim *, J Tenenbaum *, Peter Battaglia

AIIDE

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Relational inductive biases, deep learning, and graph networks

Peter Battaglia, Jess Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gülçehre, Francis Song, Andy Ballard, Justin Gilmer *, George Dahl *, Ashish Vaswani *, Kelsey Allen *, Charlie Nash, V Langston, Nicolas Heess, Chris Dyer, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yazhe Li, Razvan Pascanu

arXiv

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Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents

Joel Leibo, Cyprien de Masson d'Autume, Daniel Zoran, David Amos, Charlie Beattie, Keith Anderson, Antonio García Castañeda, Manuel Sanchez, Simon Green, Audrunas Gruslys, Shane Legg, Demis Hassabis, Matt Botvinick

arXiv

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PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations

Rico Jonschkowski, Roland Hafner, Jonathan Scholz, Martin Riedmiller

RSS

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The Future of Memory: Remembering, Imagining, and the Brain

D Schacter *, D Addis *, Demis Hassabis, V Martin *, N Spreng *, K Szpunar *

Neuron

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Publications

Simulations