1.6k citations · 9.7k across the 222 of their papers we have counts for
3 papers · 2 filters
A Compositional Object-Based Approach to Learning Physical Dynamics
Michael B. Chang, Tomer Ullman, Antonio Torralba +1
We present the Neural Physics Engine (NPE), a framework for learning simulators of intuitive physics that naturally generalize across variable object count and different scene conf…
A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding
Renqiao Zhang, Jiajun Wu, Chengkai Zhang +2
Humans demonstrate remarkable abilities to predict physical events in complex scenes. Two classes of models for physical scene understanding have recently been proposed: "Intuitive…
Modeling Human Ad Hoc Coordination
Peter M. Krafft, Chris L. Baker, Alex Pentland +1
Whether in groups of humans or groups of computer agents, collaboration is most effective between individuals who have the ability to coordinate on a joint strategy for collective…