Publications (9)
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…
A MultiPath Network for Object Detection
Sergey Zagoruyko, Adam Lerer, Tsung-Yi Lin +4
The recent COCO object detection dataset presents several new challenges for object detection. In particular, it contains objects at a broad range of scales, less prototypical imag…
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
Remi Denton, Sam Gross, Rob Fergus
We introduce a simple semi-supervised learning approach for images based on in-painting using an adversarial loss. Images with random patches removed are presented to a generator w…
Learning Physical Intuition of Block Towers by Example
Adam Lerer, Sam Gross, Rob Fergus
Wooden blocks are a common toy for infants, allowing them to develop motor skills and gain intuition about the physical behavior of the world. In this paper, we explore the ability…
Real or Fake? Learning to Discriminate Machine from Human Generated Text
Anton Bakhtin, Sam Gross, Myle Ott +3
Energy-based models (EBMs), a.k.a. un-normalized models, have had recent successes in continuous spaces. However, they have not been successfully applied to model text sequences. W…
Residual Energy-Based Models for Text
Anton Bakhtin, Yuntian Deng, Sam Gross +3
Current large-scale auto-regressive language models display impressive fluency and can generate convincing text. In this work we start by asking the question: Can the generations o…
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Myle Ott, Sergey Edunov, Alexei Baevski +5
fairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text…
Deep Counterfactual Regret Minimization
Noam Brown, Adam Lerer, Sam Gross +1
Counterfactual Regret Minimization (CFR) is the leading framework for solving large imperfect-information games. It converges to an equilibrium by iteratively traversing the game t…
Hard Mixtures of Experts for Large Scale Weakly Supervised Vision
Sam Gross, Marc'Aurelio Ranzato, Arthur Szlam
Training convolutional networks (CNN's) that fit on a single GPU with minibatch stochastic gradient descent has become effective in practice. However, there is still no effective m…