112 citations · 211 across the 10 of their papers we have counts for
7 papers · 1 filter
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions
Anuj Mahajan, Mikayel Samvelyan, Lei Mao +6
We present an extended abstract for the previously published work TESSERACT [Mahajan et al., 2021], which proposes a novel solution for Reinforcement Learning (RL) in large, factor…
Active Learning under Label Shift
Eric Zhao, Anqi Liu, Animashree Anandkumar +1
We address the problem of active learning under label shift: when the class proportions of source and target domains differ. We introduce a "medial distribution" to incorporate a t…
Causal Discovery in Physical Systems from Videos
Yunzhu Li, Antonio Torralba, Animashree Anandkumar +2
Causal discovery is at the core of human cognition. It enables us to reason about the environment and make counterfactual predictions about unseen scenarios that can vastly differ…
Convolutional Tensor-Train LSTM for Spatio-temporal Learning
Jiahao Su, Wonmin Byeon, Jean Kossaifi +3
Learning from spatio-temporal data has numerous applications such as human-behavior analysis, object tracking, video compression, and physics simulation.However, existing methods s…
Learning Pose Estimation for UAV Autonomous Navigation andLanding Using Visual-Inertial Sensor Data
Francesca Baldini, Animashree Anandkumar, Richard M. Murray
In this work, we propose a new learning approach for autonomous navigation and landing of an Unmanned-Aerial-Vehicle (UAV). We develop a multimodal fusion of deep neural architectu…
Compositional Generalization with Tree Stack Memory Units
Forough Arabshahi, Zhichu Lu, Pranay Mundra +2
We study compositional generalization, viz., the problem of zero-shot generalization to novel compositions of concepts in a domain. Standard neural networks fail to a large extent…