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07/09/2020
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Undirected graphical models are compact representations of joint probabi...
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10/01/2019
Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video
Pushing is a fundamental robotic skill. Existing work has shown how to e...
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07/22/2019
A Sufficient Statistic for Influence in Structured Multiagent Environments
Making decisions in complex environments is a key challenge in artificia...
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04/13/2019
Combining Physical Simulators and Object-Based Networks for Control
Physics engines play an important role in robot planning and control; ho...
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12/19/2018
Modular meta-learning in abstract graph networks for combinatorial generalization
Modular meta-learning is a new framework that generalizes to unseen data...
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08/09/2018
Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing
An efficient, generalizable physical simulator with universal uncertaint...
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06/26/2018
Modular meta-learning
Many prediction problems, such as those that arise in the context of rob...
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05/08/2018
Finding Frequent Entities in Continuous Data
In many applications that involve processing high-dimensional data, it i...
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04/20/2017
Learning to Acquire Information
We consider the problem of diagnosis where a set of simple observations ...
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02/12/2014