P. Battaglia

发表

Relational inductive biases, deep learning, and graph networks pdf

Razvan Pascanu, H. Francis Song, Jessica B. Hamrick, 2018, ArXiv.

Simulation as an engine of physical scene understanding

Jessica B. Hamrick, J. Tenenbaum, P. Battaglia, 2013, Proceedings of the National Academy of Sciences.

Mind Games: Game Engines as an Architecture for Intuitive Physics

J. Tenenbaum, E. Spelke, P. Battaglia, 2017, Trends in Cognitive Sciences.

Graph networks as learnable physics engines for inference and control pdf

Raia Hadsell, Martin A. Riedmiller, Jost Tobias Springenberg, 2018, ICML.

Relational Deep Reinforcement Learning pdf

Razvan Pascanu, Murray Shanahan, Yujia Li, 2018, ArXiv.

Imagination-Augmented Agents for Deep Reinforcement Learning

Razvan Pascanu, Demis Hassabis, David Silver, 2017, NIPS.

Learning to Perform Physics Experiments via Deep Reinforcement Learning pdf

Misha Denil, Nando de Freitas, Tom Erez, 2016, ICLR.

Inferring mass in complex scenes by mental simulation

Jessica B. Hamrick, J. Tenenbaum, T. Griffiths, 2016, Cognition.

Learning model-based planning from scratch pdf

Razvan Pascanu, Yujia Li, Oriol Vinyals, 2017, ArXiv.

Unsupervised Learning of 3D Structure from Images

Max Jaderberg, Nicolas Heess, Shakir Mohamed, 2016, NIPS.

Relevant and Robust

Michael C. Frank, Jessica B. Hamrick, Noah D. Goodman, 2015, Psychological science.

Discovering objects and their relations from entangled scene representations pdf

Razvan Pascanu, Timothy P. Lillicrap, Adam Santoro, 2017, ICLR.

Metacontrol for Adaptive Imagination-Based Optimization pdf

Razvan Pascanu, Jessica B. Hamrick, Oriol Vinyals, 2017, ICLR.

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017

Tom Schaul, Nando de Freitas, Shane Legg, 2017, 1711.08378.

Visual Interaction Networks: Learning a Physics Simulator from Video

Razvan Pascanu, Andrea Tacchetti, Theophane Weber, 2017, NIPS.

Relational Forward Models for Multi-Agent Learning pdf

H. Francis Song, Thore Graepel, Pedro A. M. Mediano, 2018, ICLR.

Hyperbolic Attention Networks pdf

Razvan Pascanu, Misha Denil, Nando de Freitas, 2018, ICLR.

Humans predict liquid dynamics using probabilistic simulation

Joshua B. Tenenbaum, Peter W. Battaglia, Ilker Yildirim, 2015, CogSci.

Causal Reasoning from Meta-reinforcement Learning pdf

Zeb Kurth-Nelson, Silvia Chiappa, Matthew Botvinick, 2019, ArXiv.

Learning Deep Generative Models of Graphs pdf

Razvan Pascanu, Yujia Li, Chris Dyer, 2018, ICLR 2018.

Probabilistic internal physics models guide judgments about object dynamics

Jessica B. Hamrick, Joshua B. Tenenbaum, Peter W. Battaglia, 2011, CogSci.

Humans Trade Off Viewing Time and Movement Duration to Improve Visuomotor Accuracy in a Fast Reaching Task

Peter W Battaglia, Paul R Schrater, P. Battaglia, 2007, The Journal of Neuroscience.

LanczosNet : Multi-Scale Deep Graph Convolutional Networks

Jessica B. Hamrick, B. Schölkopf, P. Battaglia, 2018 .

CompILE: Compositional Imitation Learning and Execution

Pushmeet Kohli, Edward Grefenstette, Hanjun Dai, 2018, ICML.

Bayesian integration of visual and auditory signals for spatial localization.

Robert A Jacobs, Richard N Aslin, Peter W Battaglia, 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

Object-oriented state editing for HRL pdf

Jessica B. Hamrick, Satinder Singh, Victor Bapst, 2019, ArXiv.

Agent RFM 횷 Teammate Action Prediction Egocentric Observations Action Reward Environment Environment Graph Teammate ActionStop Gradient Augmented Observations

Neil C. Rabinowitz, H. F. Song, P. Battaglia, 2019 .

DEEP REINFORCEMENT LEARNING

Tejas D. Kulkarni, T. Erez, N. D. Freitas, 2016 .

LARGE-SCALE NODE CLASSIFICATION WITH BOOTSTRAPPING

D. Budden, P. Battaglia, Alvaro Sanchez-Gonzalez, 2021 .

Different Physical Intuitions Exist Between Tasks, Not Domains

Kevin A. Smith, P. Battaglia, E. Vul, 2018, Computational Brain & Behavior.

Human Wagering Behavior Depends on Opponents' Faces

K. Nakayama, P. Battaglia, Colin Camerer, 2010, PloS one.

Probabilistic Models of Physical Reasoning

Jessica B. Hamrick, Kevin A. Smith, Adam N. Sanborn, 2020 .

Computational Models of Intuitive Physics - eScholarship

Kenneth D. Forbus, Adam N. Sanborn, J. Tenenbaum, 2012 .

Probabilistic sensorimotor processing: Overcoming uncertainty and ambiguity to improve behavior

P. Battaglia, 2008 .

Robust Bayesian framework for modeling psychophysical tasks

Paul R. Schrater, Peter W. Battaglia, P. Battaglia, 2008 .

Learned Coarse Models for Efficient Turbulence Simulation

T. Pfaff, P. Battaglia, Alvaro Sanchez-Gonzalez, 2021, ArXiv.

Pre-training via Denoising for Molecular Property Prediction

James Martens, Y. Teh, P. Battaglia, 2022, ArXiv.

Learning Symbolic Physics with Graph Networks

P. Battaglia, S. Ho, M. Cranmer, 2019, ArXiv.

Intuitive physics judgments guided by probabilistic dynamics model

Jessica B. Hamrick, Joshua B. Tenenbaum, Peter W. Battaglia, 2013 .

Inferring mass in complex physical scenes via probabilistic simulation

Thomas L. Griffiths, Jessica B. Hamrick, Joshua B. Tenenbaum, 2013, CogSci.

Intuitive mechanics in visual reasoning about complex scenes with unknown forces

Jessica B. Hamrick, Joshua B. Tenenbaum, Peter W. Battaglia, 2012 .

Physics knowledge aids object perception in dynamic scenes

Jessica B. Hamrick, Joshua B. Tenenbaum, Peter W. Battaglia, 2012 .

Partially Structured Synaptic Transitions

P. Battaglia, 1994 .

TF-GNN: Graph Neural Networks in TensorFlow

P. Battaglia, Alvaro Sanchez-Gonzalez, V. Mirrokni, 2022, ArXiv.

Intuitive physics learning in a deep-learning model inspired by developmental psychology

A. Weinstein, P. Battaglia, M. Botvinick, 2022, Nature Human Behaviour.

Learned Force Fields Are Ready For Ground State Catalyst Discovery

P. Battaglia, J. Kirkpatrick, M. Rivière, 2022, ArXiv.

L EARNED C OARSE M ODELS FOR E FFICIENT T URBULENCE S IMULATION

T. Pfaff, P. Battaglia, Alvaro Sanchez-Gonzalez, 2022 .

Imagination-Based Decision Making with Physical Models in Deep Neural Networks

Jessica B. Hamrick, Oriol Vinyals, N. Heess, 2016 .

AlignNet: Self-supervised Alignment Module

Murray Shanahan, Antonia Creswell, Peter W. Battaglia, 2019 .

Pre-training via Denoising for Molecular Property Prediction

James Martens, Y. Teh, P. Battaglia, 2022, ICLR.

Learning Symbolic Physics with Graph Networks

P. Battaglia, S. Ho, M. Cranmer, 2019, ArXiv.

The role of generative knowledge in object perception

P. Battaglia, D. Kersten, P. Schrater, 2009 .

MultiScale MeshGraphNets

T. Pfaff, A. Pritzel, P. Battaglia, 2022, ArXiv.

L EARNING GENERAL - PURPOSE CNN- BASED SIMULA TORS FOR ASTROPHYSICAL TURBULENCE

T. Pfaff, P. Battaglia, Alvaro Sanchez-Gonzalez, 2021 .

GraphCast: Learning skillful medium-range global weather forecasting

Suman V. Ravuri, Oriol Vinyals, Timo Ewalds, 2022, ArXiv.

Unifying Grokking and Double Descent

Jessica B. Hamrick, George E. Dahl, Daan Wierstra, 2023, ArXiv.

Learning rigid dynamics with face interaction graph networks

Kelsey R. Allen, William F. Whitney, T. Pfaff, 2022, ICLR.

Continuous Latent Search for Combinatorial Optimization

T. Lillicrap, Vinod Nair, P. Battaglia, 2021 .

Consistent physics underlying ballistic motion prediction

Kevin A. Smith, Ed Vul, Peter W. Battaglia, 2013, CogSci.

Interaction Networks for Learning about Objects, Relations and Physics

Razvan Pascanu, Koray Kavukcuoglu, Matthew Lai, 2016, NIPS.

Within- and Cross-Modal Distance Information Disambiguate Visual Size-Change Perception

Paul R. Schrater, Marc O. Ernst, Tonja Machulla, 2010, PLoS Comput. Biol..

Graph neural networks in particle physics

Jonathan Shlomi, Jean-Roch Vlimant, Peter Battaglia, 2020, Mach. Learn. Sci. Technol..

Learning to Simulate Complex Physics with Graph Networks

Jure Leskovec, Rex Ying, Tobias Pfaff, 2020, ICML.

Discovering Symbolic Models from Deep Learning with Inductive Biases pdf

Rui Xu, Kyle Cranmer, Miles Cranmer, 2020, NeurIPS.

Learning Mesh-Based Simulation with Graph Networks

T. Pfaff, P. Battaglia, Alvaro Sanchez-Gonzalez, 2020, International Conference on Learning Representations.

Advancing mathematics by guiding human intuition with AI

D. Hassabis, Lars Buesing, Pushmeet Kohli, 2021, Nature.

Graph network simulators can learn discontinuous, rigid contact dynamics

Kelsey R. Allen, T. Pfaff, P. Battaglia, 2022, CoRL.

ETA Prediction with Graph Neural Networks in Google Maps

Xueying Guo, Oliver Lange, Todd Hester, 2021, CIKM.

A simple neural network module for relational reasoning

Razvan Pascanu, Timothy P. Lillicrap, Adam Santoro, 2017, NIPS.

Structured agents for physical construction

Jessica B. Hamrick, Pushmeet Kohli, Carl Doersch, 2019, ICML.

Relational inductive bias for physical construction in humans and machines pdf

Jessica B. Hamrick, Joshua B. Tenenbaum, Kelsey R. Allen, 2018, CogSci.

Different Physical Intuitions Exist Between Tasks, Not Domains

Kevin A. Smith, P. Battaglia, E. Vul, 2018, Computational Brain & Behavior.

Lagrangian Neural Networks pdf

Miles Cranmer, Shirley Ho, Sam Greydanus, 2020, ICLR 2020.

Learning ground states of quantum Hamiltonians with graph networks pdf

Tobias Pfaff, Alvaro Sanchez-Gonzalez, Bryan K. Clark, 2021, ArXiv.

Deep reinforcement learning with relational inductive biases

Razvan Pascanu, Murray Shanahan, Yujia Li, 2018, ICLR.

Hamiltonian Graph Networks with ODE Integrators pdf

Kyle Cranmer, Victor Bapst, Alvaro Sanchez-Gonzalez, 2019, ArXiv.

Transframer: Arbitrary Frame Prediction with Generative Models

P. Battaglia, Mateusz Malinowski, João Carreira, 2022, Trans. Mach. Learn. Res..

Generating Images with Sparse Representations pdf

Sander Dieleman, Jacob Menick, Peter W. Battaglia, 2021, ICML.

Simple GNN Regularisation for 3D Molecular Property Prediction&Beyond

P. Battaglia, Alvaro Sanchez-Gonzalez, J. Kirkpatrick, 2021, 2106.07971.

Physical Design using Differentiable Learned Simulators

Jessica B. Hamrick, Kelsey R. Allen, T. Pfaff, 2022, ArXiv.

A Bayesian neural network predicts the dissolution of compact planetary systems pdf

Miles Cranmer, Shirley Ho, Hanno Rein, 2021, Proceedings of the National Academy of Sciences.

Graph Networks with Spectral Message Passing pdf

Peter Battaglia, Jonathan Godwin, Kimberly Stachenfeld, 2020, ArXiv.

Large-scale graph representation learning with very deep GNNs and self-supervision pdf

David Budden, Alvaro Sanchez-Gonzalez, Andreea Deac, 2021, ArXiv.

Dissociating intuitive physics from intuitive psychology: Evidence from Williams syndrome

Daniel D. Dilks, Frederik S. Kamps, P. Battaglia, 2017, Cognition.

Very Deep Graph Neural Networks Via Noise Regularisation pdf

Michael Schaarschmidt, Alvaro Sanchez-Gonzalez, Peter Battaglia, 2021, ArXiv.

Predicting the long-term stability of compact multiplanet systems

Miles Cranmer, Shirley Ho, Kristen Menou, 2020, Proceedings of the National Academy of Sciences.

PolyGen: An Autoregressive Generative Model of 3D Meshes

S. M. Ali Eslami, Peter W. Battaglia, Charlie Nash, 2020, ICML.

Constraint-based graph network simulator

T. Pfaff, P. Battaglia, Alvaro Sanchez-Gonzalez, 2021, ICML.

Graph neural networks at the Large Hadron Collider

P. Battaglia, C. Biscarat, J. Vlimant, 2023, Nature Reviews Physics.

Combining Q-Learning and Search with Amortized Value Estimates

Jessica B. Hamrick, T. Pfaff, T. Weber, 2019, ICLR.

A resource-rational model of physical abstraction for efficient mental simulation

Jessica B. Hamrick, Jan Balaguer, Matthew Botvinick, 2019, Annual Meeting of the Cognitive Science Society.

Modeling human intuitions about liquid flow with particle-based simulation

Joshua B. Tenenbaum, Peter W. Battaglia, Ilker Yildirim, 2018, PLoS Comput. Biol..

The Multi-Entity Variational Autoencoder

Christopher P. Burgess, T. Weber, P. Battaglia, 2018 .

How Haptic Size Sensations Improve Distance Perception

Paul R. Schrater, Daniel J. Kersten, Peter W. Battaglia, 2011, PLoS Comput. Biol..

Rediscovering orbital mechanics with machine learning

P. Battaglia, N. Jeffrey, P. Lemos, 2022, Machine Learning: Science and Technology.

Estimating the Material Properties of Fabric from Video

William T. Freeman, Katherine L. Bouman, Peter W. Battaglia, 2013, 2013 IEEE International Conference on Computer Vision.

Learning latent field dynamics of PDEs

Jamie A. Smith, T. Pfaff, P. Battaglia, 2020 .

Depth-dependent blur adaptation

Robert A. Jacobs, Richard N. Aslin, Peter W. Battaglia, 2004, Vision Research.

Learning Visual Question Answering by Bootstrapping Hard Attention pdf

Carl Doersch, Adam Santoro, Peter W. Battaglia, 2018, ECCV.

Within- and cross-modal distance information disambiguate visual size- perception

Paul R. Schrater, Marc O. Ernst, Daniel Kersten, 2010 .

Auxiliary object knowledge influences visually-guided interception behavior

Paul R. Schrater, Daniel J. Kersten, Peter W. Battaglia, 2005, APGV '05.

P RE - TRAINING VIA D ENOISING FOR M OLECULAR P ROPERTY P REDICTION

James Martens, Y. Teh, P. Battaglia, 2023 .

TF-GNN: Graph Neural Networks in TensorFlow

P. Battaglia, Alvaro Sanchez-Gonzalez, V. Mirrokni, 2022, ArXiv.

Human Wagering Behavior Depends on Opponents ' Faces Citation Schlicht

K. Nakayama, P. Battaglia, Colin Camerer, 2010 .

Under review as a conference paper at ICLR 2017 D ISCOVERING OBJECTS AND THEIR RELATIONS FROM ENTANGLED SCENE REPRESENTATIONS

T. Lillicrap, P. Battaglia, David Raposo, 2016 .

Inverse Design for Fluid-Structure Interactions using Graph Network Simulators

Jessica B. Hamrick, Kelsey R. Allen, T. Pfaff, 2022, NeurIPS.

Learned Simulators for Turbulence

T. Pfaff, P. Battaglia, Alvaro Sanchez-Gonzalez, 2022, ICLR.

Compositional Imitation Learning: Explaining and executing one task at a time pdf

Pushmeet Kohli, Edward Grefenstette, Hanjun Dai, 2018, ArXiv.

Exploring the triad of behaviour, genes and neuronal networks: Heritability of instrumental conditioning and the Arc/Arg3.1 gene in hippocampal coding

P. Battaglia, J. Lankelma, H. Malkki, 2013 .

Visual Interaction Networks: Learning a Physics Simulator from Video pdf

Razvan Pascanu, Andrea Tacchetti, Theophane Weber, 2017, NIPS.

R EDISCOVERING N EWTON ’ S GRAVITY AND S OLAR S YSTEM PROPERTIES USING DEEP LEARNING AND IN DUCTIVE BIASES

P. Battaglia, N. Jeffrey, Rediscovering NEWTON’S, 2021 .

Relational inductive biases, deep learning, and graph networks

Jessica B. Hamrick, Kelsey R. Allen, George E. Dahl, 2018, ArXiv.

Combining Q-Learning and Search with Amortized Value Estimates

Jessica B. Hamrick, T. Pfaff, T. Weber, 2019, ICLR.

WeatherBench 2: A benchmark for the next generation of data-driven global weather models

P. Battaglia, Alvaro Sanchez-Gonzalez, C. Bromberg, 2023, ArXiv.