
Humanrobot comanipulation of extended objects: Datadriven models and control from analysis of humanhuman dyads
Human teams are able to easily perform collaborative manipulation tasks....
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Using Logical Specifications of Objectives in MultiObjective Reinforcement Learning
In the multiobjective reinforcement learning (MORL) paradigm, the relat...
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Wasserstein Neural Processes
Neural Processes (NPs) are a class of models that learn a mapping from a...
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Video Extrapolation with an Invertible Linear Embedding
We predict future video frames from complex dynamic scenes, using an inv...
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Graph Neural Processes: Towards Bayesian Graph Neural Networks
We introduce Graph Neural Processes (GNP), inspired by the recent work i...
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Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs
As autonomous agents become more ubiquitous, they will eventually have t...
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Embedding Grammars
Classic grammars and regular expressions can be used for a variety of pu...
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Probabilistic programs for inferring the goals of autonomous agents
Intelligent systems sometimes need to infer the probable goals of people...
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What can you do with a rock? Affordance extraction via word embeddings
Autonomous agents must often detect affordances: the set of behaviors en...
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Automated Variational Inference in Probabilistic Programming
We present a new algorithm for approximate inference in probabilistic pr...
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Predictive LinearGaussian Models of Stochastic Dynamical Systems
Models of dynamical systems based on predictive state representations (P...
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The Infinite Latent Events Model
We present the Infinite Latent Events Model, a nonparametric hierarchica...
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David Wingate
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