Intuitive Physics
NIPS Workshop, 09 December 2016, Barcelona, Spain
Accepted Papers
Oral Presentations
Imagination-Based Decision Making with Physical Models in Deep Neural Networks Jessica B Hamrick, Razvan Pascanu, Oriol Vinyals, Andy Ballard, Nicolas Heess, Peter Battaglia
Deep Visual Foresight for Planning Robot Motion Chelsea Finn, Sergey Levine
Visual Stability Prediction and Its Application to Manipulation Wenbin Li, Ales Leonardis, Mario Fritz
Posters
A Differentiable Physics Engine for Deep Learning Jonas Degrave, Joni Dambre, Francis wyffels
Predicting the Dynamics of 2D Objects with a Deep Residual Network Francois Fleuret
Machine Solver for Physics Word Problems Megan Leszczynski, Jose Moreira
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
Long Term Boundary Extrapolation for Deterministic Motion Apratim Bhattacharyya, Mateusz Malinowski, Mario Fritz
Rapid Physical Predictions from Convolutional Neural Networks Filipe de A B Peres, Kevin A Smith, Joshua B Tenenbaum
Probabilistic Simulation Predicts Human Performance on Viscous Fluid-Pouring Problem James Kubricht, Chenfanfu Jiang, Yixin Zhu, Song-Chun Zhu, Demetri Terzopoulos, Hongjing Lu
A Compositional Object-Based Approach to Learning Physical Dynamics Michael Chang, Tomer Ullman, Antonio Torralba, and Joshua B Tenenbaum
Extrapolation and Learning Equations Georg Martius, Christoph H Lampert
Supervised Learning for Controlling Fluids Zherong Pan, Dinesh Manocha
Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation Ashvin Nair, Pulkit Agrawal, Dian Chen, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine
Label-Free Supervision of Neural Networks with Physics and Domain Knowledge Russell Stewart, Stefano Ermon
Learning to Perform Physics Experiments via Deep Reinforcement Learning Misha Denil, Pulkit Agrawal, Tejas Kulkarni, Tom Erez, Peter Battaglia, Nando de Freitas
A Physically-Grounded and Data-Efficient Approach to Motion Prediction Using Black-Box Optimization Shaojun Zhu, Abdeslam Boularias