A Compositional Object-Based Approach to Learning Physical Dynamics

1 December 2016

Antonio Torralba

Papers citing "A Compositional Object-Based Approach to Learning Physical Dynamics"

50 / 258 papers shown

Title
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking Eric Crawford Joelle Pineau 50 66 0 20 Nov 2019
Radically Compositional Cognitive Concepts T. S. C. Smithe CoGe 20 0 0 14 Nov 2019
Driving Reinforcement Learning with Models Meghana Rathi P. Ferraro G. Russo 15 10 0 11 Nov 2019
Estimation and Exploitation of Objects' Inertial Parameters in Robotic Grasping and Manipulation: A Survey Nikos Mavrakis Rustam Stolkin 11 47 0 11 Nov 2019
Entity Abstraction in Visual Model-Based Reinforcement Learning Rishi Veerapaneni John D. Co-Reyes Michael Chang Michael Janner Chelsea Finn Jiajun Wu J. Tenenbaum Sergey Levine OCL OffRL 43 188 0 28 Oct 2019
Learning Compositional Koopman Operators for Model-Based Control Yunzhu Li Hao He Jiajun Wu Dina Katabi Antonio Torralba 32 113 0 18 Oct 2019
Object-centric Forward Modeling for Model Predictive Control Yufei Ye Dhiraj Gandhi Abhinav Gupta Shubham Tulsiani LM&Ro OCL 20 38 0 08 Oct 2019
Structured Object-Aware Physics Prediction for Video Modeling and Planning Jannik Kossen Karl Stelzner Marcel Hussing C. Voelcker Kristian Kersting OCL 29 70 0 06 Oct 2019
Making sense of sensory input Maciej Wołczyk Jacek Tabor Johannes Welbl Szymon Maszke Marek Sergot 19 52 0 05 Oct 2019
CLEVRER: CoLlision Events for Video REpresentation and Reasoning Kexin Yi Yuta Saito Yunzhu Li Pushmeet Kohli Jiajun Wu Antonio Torralba J. Tenenbaum NAI 43 457 0 03 Oct 2019
DiffTaichi: Differentiable Programming for Physical Simulation Yuanming Hu Luke Anderson Tzu-Mao Li Qi Sun N. Carr Jonathan Ragan-Kelley F. Durand 18 372 0 01 Oct 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 152 221 0 29 Sep 2019
Hamiltonian Graph Networks with ODE Integrators Alvaro Sanchez-Gonzalez V. Bapst Kyle Cranmer Peter W. Battaglia AI4CE 31 177 0 27 Sep 2019
CoPhy: Counterfactual Learning of Physical Dynamics Fabien Baradel Natalia Neverova J. Mille Greg Mori Christian Wolf CML AI4CE 27 97 0 26 Sep 2019
Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions Boris Knyazev Carolyn Augusta Graham W. Taylor 29 30 0 23 Sep 2019
Learning Symbolic Physics with Graph Networks M. Cranmer Rui Xu Peter W. Battaglia S. Ho PINN AI4CE 191 84 0 12 Sep 2019
Belief Regulated Dual Propagation Nets for Learning Action Effects on Groups of Articulated Objects Ahmet E. Tekden Aykut Erdem Erkut Erdem Mert Imre M. Yunus Seker Emre Ugur AI4CE 24 17 0 09 Sep 2019
Compositional Video Prediction Yufei Ye Maneesh Singh Abhinav Gupta Shubham Tulsiani 18 85 0 22 Aug 2019
Neural Re-Simulation for Generating Bounces in Single Images Carlo Innamorati Bryan C. Russell D. Kaufman and Niloy J. Mitra VGen 30 11 0 17 Aug 2019
On the difficulty of learning and predicting the long-term dynamics of bouncing objects Alberto Cenzato Alberto Testolin Marco Zorzi 14 4 0 31 Jul 2019
Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning Kelsey R. Allen Kevin A. Smith J. Tenenbaum LRM 31 108 0 22 Jul 2019
Order Matters: Shuffling Sequence Generation for Video Prediction Junyan Wang Bingzhang Hu Yang Long Yu Guan 24 12 0 20 Jul 2019
Vid2Param: Modelling of Dynamics Parameters from Video Martin Asenov Michael G. Burke Daniel Angelov Todor Davchev Kartic Subr S. Ramamoorthy VGen 14 5 0 15 Jul 2019
Estimating Mass Distribution of Articulated Objects using Non-prehensile Manipulation Niranjan Kumar Kannabiran Irfan Essa Sehoon Ha Chenxi Liu 24 4 0 09 Jul 2019
Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep Neural Networks Tae Min Lee Young-Jin Oh In-Kwon Lee AI4CE 18 6 0 09 Jul 2019
Intrinsic Motivation Driven Intuitive Physics Learning using Deep Reinforcement Learning with Intrinsic Reward Normalization Jae-Woo Choi Sung-eui Yoon AI4CE PINN 20 3 0 06 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 30 871 0 04 Jun 2019
Explainability Techniques for Graph Convolutional Networks Federico Baldassarre Hossein Azizpour GNN FAtt 33 264 0 31 May 2019
What Can Neural Networks Reason About? Keyulu Xu Jingling Li Mozhi Zhang S. Du Ken-ichi Kawarabayashi Stefanie Jegelka NAI AI4CE 27 240 0 30 May 2019
Neural Consciousness Flow Xiaoran Xu Wei Feng Zhiqing Sun Zhihong Deng GNN AI4CE 27 2 0 30 May 2019
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning Caleb Chuck Supawit Chockchowwat S. Niekum 19 14 0 27 May 2019
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video Miguel Jaques Michael G. Burke Timothy M. Hospedales VGen PINN 21 45 0 27 May 2019
Unsupervised Intuitive Physics from Past Experiences Sébastien Ehrhardt Áron Monszpart Niloy J. Mitra Andrea Vedaldi OOD PINN AI4CE SSL 43 2 0 26 May 2019
Adding Intuitive Physics to Neural-Symbolic Capsules Using Interaction Networks Michael D Kissner Helmut A. Mayer OCL PINN 16 2 0 23 May 2019
Explainable Machine Learning for Scientific Insights and Discoveries R. Roscher B. Bohn Marco F. Duarte Jochen Garcke XAI 35 659 0 21 May 2019
Let's Push Things Forward: A Survey on Robot Pushing Jochen Stüber Claudio Zito Rustam Stolkin AI4CE 22 95 0 13 May 2019
Graph Element Networks: adaptive, structured computation and memory Ferran Alet Adarsh K. Jeewajee Maria Bauzá Alberto Rodriguez Tomas Lozano-Perez L. Kaelbling AI4CE GNN 27 74 0 18 Apr 2019
Object-Oriented Dynamics Learning through Multi-Level Abstraction Guangxiang Zhu Jianhao Wang Zhizhou Ren Zichuan Lin Chongjie Zhang AI4CE 32 5 0 16 Apr 2019
Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces Senthil Purushwalkam Abhinav Gupta D. Kaufman Bryan C. Russell 3DH SSL 22 20 0 15 Apr 2019
Combining Physical Simulators and Object-Based Networks for Control Anurag Ajay Maria Bauzá Jiajun Wu Nima Fazeli J. Tenenbaum Alberto Rodriguez L. Kaelbling AI4CE 17 45 0 13 Apr 2019
Structured agents for physical construction V. Bapst Alvaro Sanchez-Gonzalez Carl Doersch Kimberly L. Stachenfeld Pushmeet Kohli Peter W. Battaglia Jessica B. Hamrick AI4CE 30 99 0 05 Apr 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 39 626 0 29 Mar 2019
On Deep Set Learning and the Choice of Aggregations Maximilian Sölch A. Akhundov Patrick van der Smagt Justin Bayer TDI 27 19 0 18 Mar 2019
Unsupervised Discovery of Parts, Structure, and Dynamics Zhenjia Xu Zhijian Liu Chen Sun Kevin Patrick Murphy William T. Freeman J. Tenenbaum Jiajun Wu OCL 38 61 0 12 Mar 2019
Joint Perception and Control as Inference with an Object-based Implementation Minne Li Zheng Tian Pranav Nashikkar Ian Davies Ying Wen Jun Wang 24 2 0 04 Mar 2019
Graph Neural Processes: Towards Bayesian Graph Neural Networks Andrew N. Carr David Wingate BDL 37 12 0 26 Feb 2019
Stochastic Prediction of Multi-Agent Interactions from Partial Observations Chen Sun Per Karlsson Jiajun Wu J. Tenenbaum Kevin Patrick Murphy 33 89 0 25 Feb 2019
Emulating Human Developmental Stages with Bayesian Neural Networks Marcel Binz Dominik M. Endres 10 3 0 20 Feb 2019
Differentiable Physics-informed Graph Networks Sungyong Seo Yan Liu PINN AI4CE 25 67 0 08 Feb 2019
Active Localization of Gas Leaks using Fluid Simulation Martin Asenov M. Rutkauskas D. Reid Kartic Subr S. Ramamoorthy 10 19 0 28 Jan 2019