Auxiliary object knowledge influences visually-guided interception behavior. - Peter W. Battaglia; Paul R. Schrater; Daniel J. Kersten (APGV, 2005)

Within- and Cross-Modal Distance Information Disambiguate Visual Size-Change Perception. - Peter W. Battaglia; Massimiliano Di Luca; Marc O. Ernst; Paul R. Schrater; Tonja Machulla; Daniel J. Kersten (PLoS Comput. Biol., 2010)

Probabilistic internal physics models guide judgments about object dynamics. - Jessica B. Hamrick; Peter W. Battaglia; Joshua B. Tenenbaum (CogSci, 2011)

How Haptic Size Sensations Improve Distance Perception. - Peter W. Battaglia; Daniel J. Kersten; Paul R. Schrater (PLoS Comput. Biol., 2011)

Computational Models of Intuitive Physics. - Peter W. Battaglia; Tomer D. Ullman; Joshua B. Tenenbaum; Adam Sanborn; Kenneth D. Forbus; Tobias Gerstenberg; David A. Lagnado (CogSci, 2012)

Inferring mass in complex physical scenes via probabilistic simulation. - Jessica B. Hamrick; Peter W. Battaglia; Thomas L. Griffiths 001; Joshua B. Tenenbaum (CogSci, 2013)

Consistent physics underlying ballistic motion prediction. - Kevin A. Smith 001; Peter W. Battaglia; Edward Vul (CogSci, 2013)

Estimating the Material Properties of Fabric from Video. - Katherine L. Bouman; Bei Xiao; Peter W. Battaglia; William T. Freeman (ICCV, 2013)

Humans predict liquid dynamics using probabilistic simulation. - Christopher Bates; Peter W. Battaglia; Ilker Yildirim; Joshua B. Tenenbaum (CogSci, 2015)

Interaction Networks for Learning about Objects, Relations and Physics. - Peter W. Battaglia; Razvan Pascanu; Matthew Lai; Danilo Jimenez Rezende; Koray Kavukcuoglu (NIPS, 2016)

Unsupervised Learning of 3D Structure from Images. - Danilo Jimenez Rezende; S. M. Ali Eslami; Shakir Mohamed; Peter W. Battaglia; Max Jaderberg; Nicolas Heess (NIPS, 2016)

Tutorial: Recent Advances in Deep Learning. - Matthew M. Botvinick; Peter W. Battaglia (CogSci, 2017)

A model of structure learning, inference, and generation for scene understanding. - David Raposo; Peter Dayan; Demis Hassabis; Peter W. Battaglia (CogSci, 2017)

Learning to Perform Physics Experiments via Deep Reinforcement Learning. - Misha Denil; Pulkit Agrawal 001; Tejas D. Kulkarni; Tom Erez; Peter W. Battaglia; Nando de Freitas (ICLR (Poster), 2017)

Metacontrol for Adaptive Imagination-Based Optimization. - Jessica B. Hamrick; Andrew J. Ballard; Razvan Pascanu; Oriol Vinyals; Nicolas Heess; Peter W. Battaglia (ICLR (Poster), 2017)

Discovering objects and their relations from entangled scene representations. - David Raposo; Adam Santoro; David G. T. Barrett; Razvan Pascanu; Tim Lillicrap; Peter W. Battaglia (ICLR (Workshop), 2017)

Imagination-Augmented Agents for Deep Reinforcement Learning. - Sébastien Racanière; Theophane Weber; David P. Reichert; Lars Buesing; Arthur Guez; Danilo Jimenez Rezende; Adrià Puigdomènech Badia; Oriol Vinyals; Nicolas Heess; Yujia Li 001; Razvan Pascanu; Peter W. Battaglia; et al. (NIPS, 2017)

A simple neural network module for relational reasoning. - Adam Santoro; David Raposo; David G. T. Barrett; Mateusz Malinowski; Razvan Pascanu; Peter W. Battaglia; Tim Lillicrap (NIPS, 2017)

Visual Interaction Networks: Learning a Physics Simulator from Video. - Nicholas Watters; Daniel Zoran; Theophane Weber; Peter W. Battaglia; Razvan Pascanu; Andrea Tacchetti (NIPS, 2017)

Learning model-based planning from scratch. - Razvan Pascanu; Yujia Li 001; Oriol Vinyals; Nicolas Heess; Lars Buesing; Sébastien Racanière; David P. Reichert; Theophane Weber; Daan Wierstra; Peter W. Battaglia (CoRR, 2017)

Visual Interaction Networks. - Nicholas Watters; Andrea Tacchetti; Theophane Weber; Razvan Pascanu; Peter W. Battaglia; Daniel Zoran (CoRR, 2017)

Imagination-Augmented Agents for Deep Reinforcement Learning. - Theophane Weber; Sébastien Racanière; David P. Reichert; Lars Buesing; Arthur Guez; Danilo Jimenez Rezende; Adrià Puigdomènech Badia; Oriol Vinyals; Nicolas Heess; Yujia Li 001; Razvan Pascanu; Peter W. Battaglia; et al. (CoRR, 2017)

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. - Matthew M. Botvinick; David G. T. Barrett; Peter W. Battaglia; Nando de Freitas; Dharshan Kumaran; Joel Z. Leibo; Tim Lillicrap; Joseph Modayil; S. Mohamed; Neil C. Rabinowitz; Danilo Jimenez Rezende; Adam Santoro; et al. (CoRR, 2017)

Relational inductive bias for physical construction in humans and machines. - Jessica B. Hamrick; Kelsey R. Allen; Victor Bapst; Tina Zhu; Kevin R. McKee; Josh Tenenbaum 001; Peter W. Battaglia (CogSci, 2018)

Learning Visual Question Answering by Bootstrapping Hard Attention. - Mateusz Malinowski; Carl Doersch; Adam Santoro; Peter W. Battaglia (ECCV (6), 2018)

Graph Networks as Learnable Physics Engines for Inference and Control. - Alvaro Sanchez-Gonzalez; Nicolas Heess; Jost Tobias Springenberg; Josh Merel; Martin A. Riedmiller; Raia Hadsell; Peter W. Battaglia (ICML, 2018)

Learning Deep Generative Models of Graphs. - Yujia Li 001; Oriol Vinyals; Chris Dyer; Razvan Pascanu; Peter W. Battaglia (CoRR, 2018)

Relational inductive biases, deep learning, and graph networks. - Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinícius Flores Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Relational Deep Reinforcement Learning. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (CoRR, 2018)

Relational Forward Models for Multi-Agent Learning. - Andrea Tacchetti; H. Francis Song; Pedro A. M. Mediano; Vinícius Flores Zambaldi; Neil C. Rabinowitz; Thore Graepel; Matthew M. Botvinick; Peter W. Battaglia (CoRR, 2018)

Compositional Imitation Learning: Explaining and executing one task at a time. - Thomas Kipf; Yujia Li 001; Hanjun Dai; Vinícius Flores Zambaldi; Edward Grefenstette; Pushmeet Kohli; Peter W. Battaglia (CoRR, 2018)

A resource-rational model of physical abstraction for efficient mental simulation. - Tina Zhu; Jessica B. Hamrick; Kevin R. McKee; Raphael Koster; Jan Balaguer; Peter W. Battaglia; Matthew M. Botvinick (CogSci, 2019)

Hyperbolic Attention Networks. - Çaglar Gülçehre; Misha Denil; Mateusz Malinowski; Ali Razavi; Razvan Pascanu; Karl Moritz Hermann; Peter W. Battaglia; Victor Bapst; David Raposo; Adam Santoro; Nando de Freitas (ICLR (Poster), 2019)

Relational Forward Models for Multi-Agent Learning. - Andrea Tacchetti; H. Francis Song; Pedro A. M. Mediano; Vinícius Flores Zambaldi; János Kramár; Neil C. Rabinowitz; Thore Graepel; Matthew M. Botvinick; Peter W. Battaglia (ICLR (Poster), 2019)

Deep reinforcement learning with relational inductive biases. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (ICLR (Poster), 2019)

Structured agents for physical construction. - Victor Bapst; Alvaro Sanchez-Gonzalez; Carl Doersch; Kimberly L. Stachenfeld; Pushmeet Kohli; Peter W. Battaglia; Jessica B. Hamrick (ICML, 2019)

CompILE: Compositional Imitation Learning and Execution. - Thomas Kipf; Yujia Li 001; Hanjun Dai; Vinícius Flores Zambaldi; Alvaro Sanchez-Gonzalez; Edward Grefenstette; Pushmeet Kohli; Peter W. Battaglia (ICML, 2019)

Causal Reasoning from Meta-reinforcement Learning. - Ishita Dasgupta 001; Jane X. Wang; Silvia Chiappa; Jovana Mitrovic; Pedro A. Ortega; David Raposo; Edward Hughes 001; Peter W. Battaglia; Matthew M. Botvinick; Zeb Kurth-Nelson (CoRR, 2019)

Learning Symbolic Physics with Graph Networks. - Miles D. Cranmer; Rui Xu; Peter W. Battaglia; Shirley Ho (CoRR, 2019)

Hamiltonian Graph Networks with ODE Integrators. - Alvaro Sanchez-Gonzalez; Victor Bapst; Kyle Cranmer; Peter W. Battaglia (CoRR, 2019)

Object-oriented state editing for HRL. - Victor Bapst; Alvaro Sanchez-Gonzalez; Omar Shams; Kimberly L. Stachenfeld; Peter W. Battaglia; Satinder Singh 001; Jessica B. Hamrick (CoRR, 2019)

Modeling human intuitions about liquid flow with particle-based simulation. - Christopher Bates; Ilker Yildirim; Joshua B. Tenenbaum; Peter W. Battaglia (PLoS Comput. Biol., 2019)

Combining Q-Learning and Search with Amortized Value Estimates. - Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Tobias Pfaff; Theophane Weber; Lars Buesing; Peter W. Battaglia (ICLR, 2020)

PolyGen: An Autoregressive Generative Model of 3D Meshes. - Charlie Nash; Yaroslav Ganin; S. M. Ali Eslami; Peter W. Battaglia (ICML, 2020)

Learning to Simulate Complex Physics with Graph Networks. - Alvaro Sanchez-Gonzalez; Jonathan Godwin; Tobias Pfaff; Rex Ying; Jure Leskovec; Peter W. Battaglia (ICML, 2020)

Discovering Symbolic Models from Deep Learning with Inductive Biases. - Miles D. Cranmer; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Rui Xu; Kyle Cranmer; David N. Spergel; Shirley Ho (NeurIPS, 2020)

Lagrangian Neural Networks. - Miles D. Cranmer; Sam Greydanus; Stephan Hoyer; Peter W. Battaglia; David N. Spergel; Shirley Ho (CoRR, 2020)

ETA Prediction with Graph Neural Networks in Google Maps. - Austin Derrow-Pinion; Jennifer She; David Wong; Oliver Lange; Todd Hester; Luis Perez; Marc Nunkesser; Seongjae Lee; Xueying Guo; Brett Wiltshire; Peter W. Battaglia; Vishal Gupta; et al. (CIKM, 2021)

Learning Mesh-Based Simulation with Graph Networks. - Tobias Pfaff; Meire Fortunato; Alvaro Sanchez-Gonzalez; Peter W. Battaglia (ICLR, 2021)

Generating images with sparse representations. - Charlie Nash; Jacob Menick; Sander Dieleman; Peter W. Battaglia (ICML, 2021)

Graph Networks with Spectral Message Passing. - Kimberly L. Stachenfeld; Jonathan Godwin; Peter W. Battaglia (CoRR, 2021)

A Bayesian neural network predicts the dissolution of compact planetary systems. - Miles D. Cranmer; Daniel Tamayo; Hanno Rein; Peter W. Battaglia; Samuel Hadden; Philip J. Armitage; Shirley Ho; David N. Spergel (CoRR, 2021)

Very Deep Graph Neural Networks Via Noise Regularisation. - Jonathan Godwin; Michael Schaarschmidt; Alexander L. Gaunt; Alvaro Sanchez-Gonzalez; Yulia Rubanova; Petar Velickovic; James Kirkpatrick; Peter W. Battaglia (CoRR, 2021)

Large-scale graph representation learning with very deep GNNs and self-supervision. - Ravichandra Addanki; Peter W. Battaglia; David Budden; Andreea Deac; Jonathan Godwin; Thomas Keck; Wai Lok Sibon Li; Alvaro Sanchez-Gonzalez; Jacklynn Stott; Shantanu Thakoor; Petar Velickovic (CoRR, 2021)

Learning ground states of quantum Hamiltonians with graph networks. - Dmitrii Kochkov; Tobias Pfaff; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Bryan K. Clark (CoRR, 2021)

Learned Coarse Models for Efficient Turbulence Simulation. - Kimberly L. Stachenfeld; Drummond B. Fielding; Dmitrii Kochkov; Miles D. Cranmer; Tobias Pfaff; Jonathan Godwin; Can Cui; Shirley Ho; Peter W. Battaglia; Alvaro Sanchez-Gonzalez (CoRR, 2021)

Graph neural networks in particle physics. - Jonathan Shlomi; Peter W. Battaglia; Jean-Roch Vlimant (Mach. Learn. Sci. Technol., 2021)

Advancing mathematics by guiding human intuition with AI. - Alex Davies; Petar Velickovic; Lars Buesing; Sam Blackwell; Daniel Zheng; Nenad Tomasev; Richard Tanburn; Peter W. Battaglia; Charles Blundell; András Juhász; Marc Lackenby; Geordie Williamson; et al. (Nat., 2021)

Graph network simulators can learn discontinuous, rigid contact dynamics. - Kelsey R. Allen; Tatiana Lopez-Guevara; Yulia Rubanova; Kimberly L. Stachenfeld; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Tobias Pfaff (CoRL, 2022)

Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond. - Jonathan Godwin; Michael Schaarschmidt; Alexander L. Gaunt; Alvaro Sanchez-Gonzalez; Yulia Rubanova; Petar Velickovic; James Kirkpatrick; Peter W. Battaglia (ICLR, 2022)

Learned Simulators for Turbulence. - Kimberly L. Stachenfeld; Drummond Buschman Fielding; Dmitrii Kochkov; Miles D. Cranmer; Tobias Pfaff; Jonathan Godwin; Can Cui; Shirley Ho; Peter W. Battaglia; Alvaro Sanchez-Gonzalez (ICLR, 2022)

Constraint-based graph network simulator. - Yulia Rubanova; Alvaro Sanchez-Gonzalez; Tobias Pfaff; Peter W. Battaglia (ICML, 2022)

Inverse Design for Fluid-Structure Interactions using Graph Network Simulators. - Kelsey R. Allen; Tatiana Lopez-Guevara; Kimberly L. Stachenfeld; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Jessica B. Hamrick; Tobias Pfaff (NeurIPS, 2022)

Physical Design using Differentiable Learned Simulators. - Kelsey R. Allen; Tatiana Lopez-Guevara; Kimberly L. Stachenfeld; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Jessica B. Hamrick; Tobias Pfaff (CoRR, 2022)

TF-GNN: Graph Neural Networks in TensorFlow. - Oleksandr Ferludin; Arno Eigenwillig; Martin Blais; Dustin Zelle; Jan Pfeifer; Alvaro Sanchez-Gonzalez; Wai Lok Sibon Li; Sami Abu-El-Haija; Peter W. Battaglia; Neslihan Bulut; Jonathan Halcrow; Filipe Miguel Gonçalves de Almeida; et al. (CoRR, 2022)

Learned Force Fields Are Ready For Ground State Catalyst Discovery. - Michael Schaarschmidt; Morgane Riviere; Alex M. Ganose; James S. Spencer; Alexander L. Gaunt; James Kirkpatrick; Simon Axelrod; Peter W. Battaglia; Jonathan Godwin (CoRR, 2022)

MultiScale MeshGraphNets. - Meire Fortunato; Tobias Pfaff; Peter Wirnsberger; Alexander Pritzel; Peter W. Battaglia (CoRR, 2022)

GraphCast: Learning skillful medium-range global weather forecasting. - Rémi Lam; Alvaro Sanchez-Gonzalez; Matthew Willson; Peter Wirnsberger; Meire Fortunato; Alexander Pritzel; Suman V. Ravuri; Timo Ewalds; Ferran Alet; Zach Eaton-Rosen; Weihua Hu; Alexander Merose; et al. (CoRR, 2022)

Learning rigid dynamics with face interaction graph networks. - Kelsey R. Allen; Yulia Rubanova; Tatiana Lopez-Guevara; William Whitney 001; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Tobias Pfaff (ICLR, 2023)

Pre-training via Denoising for Molecular Property Prediction. - Sheheryar Zaidi; Michael Schaarschmidt; James Martens; Hyunjik Kim; Yee Whye Teh; Alvaro Sanchez-Gonzalez; Peter W. Battaglia; Razvan Pascanu; Jonathan Godwin (ICLR, 2023)

WeatherBench 2: A benchmark for the next generation of data-driven global weather models. - Stephan Rasp 001; Stephan Hoyer; Alexander Merose; Ian Langmore; Peter W. Battaglia; Tyler Russell; Alvaro Sanchez-Gonzalez; Vivian Yang; Rob Carver; Shreya Agrawal; Matthew Chantry; Zied Ben Bouallegue; et al. (CoRR, 2023)

Diffusion Generative Inverse Design. - Marin Vlastelica; Tatiana Lopez-Guevara; Kelsey R. Allen; Peter W. Battaglia; Arnaud Doucet; Kimberly L. Stachenfeld (CoRR, 2023)

Neural General Circulation Models. - Dmitrii Kochkov; Janni Yuval; Ian Langmore; Peter C. Norgaard; Jamie A. Smith; Griffin Mooers; James Lottes; Stephan Rasp 001; Peter D. Düben; Milan Klöwer; Sam Hatfield; Peter W. Battaglia; et al. (CoRR, 2023)

GenCast: Diffusion-based ensemble forecasting for medium-range weather. - Ilan Price; Alvaro Sanchez-Gonzalez; Ferran Alet; Timo Ewalds; Andrew El-Kadi; Jacklynn Stott; Shakir Mohamed; Peter W. Battaglia; Rémi Lam; Matthew Willson (CoRR, 2023)

Transframer: Arbitrary Frame Prediction with Generative Models. - Charlie Nash; João Carreira 001; Jacob C. Walker; Iain Barr; Andrew Jaegle; Mateusz Malinowski; Peter W. Battaglia (Trans. Mach. Learn. Res., 2023)

Rediscovering orbital mechanics with machine learning. - Pablo Lemos; Niall Jeffrey; Miles D. Cranmer; Shirley Ho; Peter W. Battaglia (Mach. Learn. Sci. Technol., 2023)

Neural general circulation models for weather and climate. - Dmitrii Kochkov; Janni Yuval; Ian Langmore; Peter C. Norgaard; Jamie A. Smith; Griffin Mooers; Milan Klöwer; James Lottes; Stephan Rasp 001; Peter D. Düben; Sam Hatfield; Peter W. Battaglia; et al. (Nat., 2024)

Probabilistic weather forecasting with machine learning. - Ilan Price; Alvaro Sanchez-Gonzalez; Ferran Alet; Tom R. Andersson; Andrew El-Kadi; Dominic Masters; Timo Ewalds; Jacklynn Stott; Shakir Mohamed; Peter W. Battaglia; Rémi R. Lam; Matthew Willson (Nat., 2025)

Skillful joint probabilistic weather forecasting from marginals. - Ferran Alet; Ilan Price; Andrew El-Kadi; Dominic Masters; Stratis Markou; Tom R. Andersson; Jacklynn Stott; Rémi Lam; Matthew Willson; Alvaro Sanchez-Gonzalez; Peter W. Battaglia (CoRR, 2025)