59 citations · 93 across the 7 of their papers we have counts for
5 papers · 1 filter
Learning Compositional Koopman Operators for Model-Based Control
Yunzhu Li, Hao He, Jiajun Wu +2
Finding an embedding space for a linear approximation of a nonlinear dynamical system enables efficient system identification and control synthesis. The Koopman operator theory lay…
Making the Invisible Visible: Action Recognition Through Walls and Occlusions
Tianhong Li, Lijie Fan, Mingmin Zhao +2
Understanding people's actions and interactions typically depends on seeing them. Automating the process of action recognition from visual data has been the topic of much research…
Harnessing Structures for Value-Based Planning and Reinforcement Learning
Yuzhe Yang, Guo Zhang, Zhi Xu +1
Value-based methods constitute a fundamental methodology in planning and deep reinforcement learning (RL). In this paper, we propose to exploit the underlying structures of the sta…
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Yuzhe Yang, Guo Zhang, Dina Katabi +1
Deep neural networks are vulnerable to adversarial attacks. The literature is rich with algorithms that can easily craft successful adversarial examples. In contrast, the performan…
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling
Hao Wang, Chengzhi Mao, Hao He +3
We consider the problem of inferring the values of an arbitrary set of variables (e.g., risk of diseases) given other observed variables (e.g., symptoms and diagnosed diseases) and…