510 citations · 1.5k across the 48 of their papers we have counts for
9 papers · 1 filter
Deep Imitation Learning for Bimanual Robotic Manipulation
Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza +3
We present a deep imitation learning framework for robotic bimanual manipulation in a continuous state-action space. A core challenge is to generalize the manipulation skills to ob…
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems
Rui Wang, Danielle Maddix, Christos Faloutsos +2
How can we learn a dynamical system to make forecasts, when some variables are unobserved? For instance, in COVID-19, we want to forecast the number of infected and death cases but…
Trajectory Prediction using Equivariant Continuous Convolution
Robin Walters, Jinxi Li, Rose Yu
Trajectory prediction is a critical part of many AI applications, for example, the safe operation of autonomous vehicles. However, current methods are prone to making inconsistent…
Dynamic Relational Inference in Multi-Agent Trajectories
Ruichao Xiao, Manish Kumar Singh, Rose Yu
Inferring interactions from multi-agent trajectories has broad applications in physics, vision and robotics. Neural relational inference (NRI) is a deep generative model that can r…
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks
Chintan Shah, Nima Dehmamy, Nicola Perra +4
Locating the source of an epidemic, or patient zero (P0), can provide critical insights into the infection's transmission course and allow efficient resource allocation. Existing m…
Learning Disentangled Representations of Video with Missing Data
Armand Comas-Massagué, Chi Zhang, Zlatan Feric +2
Missing data poses significant challenges while learning representations of video sequences. We present Disentangled Imputed Video autoEncoder (DIVE), a deep generative model that…