16.2k citations · 16.7k across the 11 of their papers we have counts for
11 papers
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa +18
Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible…
Growing Action Spaces
Gregory Farquhar, Laura Gustafson, Zeming Lin +3
In complex tasks, such as those with large combinatorial action spaces, random exploration may be too inefficient to achieve meaningful learning progress. In this work, we use a cu…
Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger
Gabriel Synnaeve, Zeming Lin, Jonas Gehring +5
We formulate the problem of defogging as state estimation and future state prediction from previous, partial observations in the context of real-time strategy games. We propose to…
Value Propagation Networks
Nantas Nardelli, Gabriel Synnaeve, Zeming Lin +3
We present Value Propagation (VProp), a set of parameter-efficient differentiable planning modules built on Value Iteration which can successfully be trained using reinforcement le…
STARDATA: A StarCraft AI Research Dataset
Zeming Lin, Jonas Gehring, Vasil Khalidov +1
We release a dataset of 65646 StarCraft replays that contains 1535 million frames and 496 million player actions. We provide full game state data along with the original replays th…
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play
Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov +3
We describe a simple scheme that allows an agent to learn about its environment in an unsupervised manner. Our scheme pits two versions of the same agent, Alice and Bob, against on…