230 citations · 1.1k across the 45 of their papers we have counts for
11 papers · 1 filter
MetaMorph: Learning Universal Controllers with Transformers
Agrim Gupta, Linxi Fan, Surya Ganguli +1
Multiple domains like vision, natural language, and audio are witnessing tremendous progress by leveraging Transformers for large scale pre-training followed by task specific fine…
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies
Linxi Fan, Guanzhi Wang, De-An Huang +4
Generalization has been a long-standing challenge for reinforcement learning (RL). Visual RL, in particular, can be easily distracted by irrelevant factors in high-dimensional obse…
Adaptive Procedural Task Generation for Hard-Exploration Problems
Kuan Fang, Yuke Zhu, Silvio Savarese +1
We introduce Adaptive Procedural Task Generation (APT-Gen), an approach to progressively generate a sequence of tasks as curricula to facilitate reinforcement learning in hard-expl…
SURREAL-System: Fully-Integrated Stack for Distributed Deep Reinforcement Learning
Linxi Fan, Yuke Zhu, Jiren Zhu +6
We present an overview of SURREAL-System, a reproducible, flexible, and scalable framework for distributed reinforcement learning (RL). The framework consists of a stack of four la…
Causal Induction from Visual Observations for Goal Directed Tasks
Suraj Nair, Yuke Zhu, Silvio Savarese +1
Causal reasoning has been an indispensable capability for humans and other intelligent animals to interact with the physical world. In this work, we propose to endow an artificial…
DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs
Yunbo Wang, Bo Liu, Jiajun Wu +4
A major difficulty of solving continuous POMDPs is to infer the multi-modal distribution of the unobserved true states and to make the planning algorithm dependent on the perceived…