Peter W. Battaglia

According to our database1, Peter W. Battaglia authored at least 47 papers between 2005 and 2020.

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Bibliography

2020
Discovering Symbolic Models from Deep Learning with Inductive Biases.
CoRR, 2020

Lagrangian Neural Networks.
CoRR, 2020

PolyGen: An Autoregressive Generative Model of 3D Meshes.
CoRR, 2020

Learning to Simulate Complex Physics with Graph Networks.
CoRR, 2020

Combining Q-Learning and Search with Amortized Value Estimates.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Object-oriented state editing for HRL.
CoRR, 2019

Hamiltonian Graph Networks with ODE Integrators.
CoRR, 2019

Learning Symbolic Physics with Graph Networks.
CoRR, 2019

Causal Reasoning from Meta-reinforcement Learning.
CoRR, 2019

CompILE: Compositional Imitation Learning and Execution.
Proceedings of the 36th International Conference on Machine Learning, 2019

Structured agents for physical construction.
Proceedings of the 36th International Conference on Machine Learning, 2019

Deep reinforcement learning with relational inductive biases.
Proceedings of the 7th International Conference on Learning Representations, 2019

Relational Forward Models for Multi-Agent Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Hyperbolic Attention Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

A resource-rational model of physical abstraction for efficient mental simulation.
Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2018
Compositional Imitation Learning: Explaining and executing one task at a time.
CoRR, 2018

Relational Forward Models for Multi-Agent Learning.
CoRR, 2018

Modeling human intuitions about liquid flow with particle-based simulation.
CoRR, 2018

Relational Deep Reinforcement Learning.
CoRR, 2018

Relational inductive biases, deep learning, and graph networks.
CoRR, 2018

Learning Deep Generative Models of Graphs.
CoRR, 2018

Graph Networks as Learnable Physics Engines for Inference and Control.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Visual Question Answering by Bootstrapping Hard Attention.
Proceedings of the Computer Vision - ECCV 2018, 2018

Relational inductive bias for physical construction in humans and machines.
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.
CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.
CoRR, 2017

Visual Interaction Networks.
CoRR, 2017

Learning model-based planning from scratch.
CoRR, 2017

Visual Interaction Networks: Learning a Physics Simulator from Video.
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.
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.
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.
Proceedings of the 5th International Conference on Learning Representations, 2017

Metacontrol for Adaptive Imagination-Based Optimization.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning to Perform Physics Experiments via Deep Reinforcement Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

A model of structure learning, inference, and generation for scene understanding.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Tutorial: Recent Advances in Deep Learning.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016
Unsupervised Learning of 3D Structure from Images.
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.
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.
Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2013
Estimating the Material Properties of Fabric from Video.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Consistent physics underlying ballistic motion prediction.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

Inferring mass in complex physical scenes via probabilistic simulation.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2012
Computational Models of Intuitive Physics.
Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011
How Haptic Size Sensations Improve Distance Perception.
PLoS Computational Biology, 2011

Probabilistic internal physics models guide judgments about object dynamics.
Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

2010
Within- and Cross-Modal Distance Information Disambiguate Visual Size-Change Perception.
PLoS Computational Biology, 2010

2005
Auxiliary object knowledge influences visually-guided interception behavior.
Proceedings of the 2nd Symposium on Applied Perception in Graphics and Visualization, 2005


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