Peter W. Battaglia

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Simulate Complex Physics with Graph Networks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

PolyGen: An Autoregressive Generative Model of 3D Meshes.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Combining Q-Learning and Search with Amortized Value Estimates.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Modeling human intuitions about liquid flow with particle-based simulation.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2019

Object-oriented state editing for HRL.

[BibT_eX]

[DOI]

Omar Shams

Kimberly L. Stachenfeld

Satinder Singh

CoRR, 2019

Hamiltonian Graph Networks with ODE Integrators.

[BibT_eX]

[DOI]

Kyle Cranmer

CoRR, 2019

Learning Symbolic Physics with Graph Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Causal Reasoning from Meta-reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

CompILE: Compositional Imitation Learning and Execution.

[BibT_eX]

[DOI]

Thomas Kipf

Yujia Li

Hanjun Dai

Edward Grefenstette

Pushmeet Kohli

Proceedings of the 36th International Conference on Machine Learning, 2019

Structured agents for physical construction.

[BibT_eX]

[DOI]

Carl Doersch

Kimberly L. Stachenfeld

Pushmeet Kohli

Proceedings of the 36th International Conference on Machine Learning, 2019

Deep reinforcement learning with relational inductive biases.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Relational Forward Models for Multi-Agent Learning.

[BibT_eX]

[DOI]

Andrea Tacchetti

H. Francis Song

Pedro A. M. Mediano

Proceedings of the 7th International Conference on Learning Representations, 2019

Hyperbolic Attention Networks.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

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

[BibT_eX]

[DOI]

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2018

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

[BibT_eX]

[DOI]

Thomas Kipf

Yujia Li

Hanjun Dai

Edward Grefenstette

Pushmeet Kohli

CoRR, 2018

Relational Forward Models for Multi-Agent Learning.

[BibT_eX]

[DOI]

Andrea Tacchetti

H. Francis Song

Pedro A. M. Mediano

CoRR, 2018

Relational Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Relational inductive biases, deep learning, and graph networks.

[BibT_eX]

[DOI]

CoRR, 2018

Learning Deep Generative Models of Graphs.

[BibT_eX]

[DOI]

CoRR, 2018

Graph Networks as Learnable Physics Engines for Inference and Control.

[BibT_eX]

[DOI]

Nicolas Heess

Jost Tobias Springenberg

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Visual Question Answering by Bootstrapping Hard Attention.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2018, 2018

Relational inductive bias for physical construction in humans and machines.

[BibT_eX]

[DOI]

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

2017

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

[BibT_eX]

[DOI]

Adam Santoro

Tom Schaul

Christopher Summerfield

CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Adrià Puigdomènech Badia

CoRR, 2017

Visual Interaction Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Learning model-based planning from scratch.

[BibT_eX]

[DOI]

CoRR, 2017

Visual Interaction Networks: Learning a Physics Simulator from Video.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A simple neural network module for relational reasoning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Adrià Puigdomènech Badia

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Discovering objects and their relations from entangled scene representations.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Metacontrol for Adaptive Imagination-Based Optimization.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Learning to Perform Physics Experiments via Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

A model of structure learning, inference, and generation for scene understanding.

[BibT_eX]

[DOI]

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Tutorial: Recent Advances in Deep Learning.

[BibT_eX]

[DOI]

Matthew M. Botvinick

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016

Unsupervised Learning of 3D Structure from Images.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Interaction Networks for Learning about Objects, Relations and Physics.

[BibT_eX]

[DOI]

Razvan Pascanu

Matthew Lai

Koray Kavukcuoglu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Humans predict liquid dynamics using probabilistic simulation.

[BibT_eX]

[DOI]

Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2013

Estimating the Material Properties of Fabric from Video.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2013

Consistent physics underlying ballistic motion prediction.

[BibT_eX]

[DOI]

Kevin A. Smith

Edward Vul

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

Inferring mass in complex physical scenes via probabilistic simulation.

[BibT_eX]

[DOI]

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2012

Computational Models of Intuitive Physics.

[BibT_eX]

[DOI]

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011

How Haptic Size Sensations Improve Distance Perception.

[BibT_eX]

[DOI]

Daniel J. Kersten

Paul R. Schrater

PLoS Comput. Biol., 2011

Probabilistic internal physics models guide judgments about object dynamics.

[BibT_eX]

[DOI]

Joshua B. Tenenbaum

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

2010

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

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2010

2005

Auxiliary object knowledge influences visually-guided interception behavior.

[BibT_eX]

[DOI]