People

Soumith Chintala

Research Engineer

Soumith Chintala is a Researcher at Facebook AI Research, where he works on deep learning, reinforcement learning, generative image models, agents for video games and large-scale high-performance deep learning. Prior to joining Facebook in August 2014, he worked at MuseAmi, where he built deep learning models for music and vision targeted at mobile devices. He holds a Masters in CS from NYU, and spent time in Yann LeCun’s NYU lab building deep learning models for pedestrian detection, natural image OCR, depth-images among others.

Interests

Meta-problems, learning embeddings, image and video understanding, music classification and natural language understanding

Latest Publications

VLDB - August 31, 2020

PyTorch Distributed: Experiences on Accelerating Data Parallel Training

Shen Li, Yanli Zhao, Rohan Verma, Omkar Salpekar, Pieter Noordhuis, Teng Li, Adam Paszke, Jeff Smith, Brian Vaughan, Pritam Damania, Soumith Chintala

NeurIPS - December 2, 2019

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala

ICML 2017 - August 6, 2017

Wasserstein Generative Adversarial Networks

Martin Arjovsky, Soumith Chintala, Léon Bottou

CVPR 2017 - July 21, 2017

Discovering Causal Signals in Images

David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Scholkopf, Léon Bottou

ICLR 2017 - April 24, 2017

Episodic Exploration for Deep Deterministic Policies for StarCraft Micro-Management

Nicolas Usunier, Gabriel Synnaeve, Zeming Lin, Soumith Chintala

NIPS Workshop - November 30, 2016

Semantic Segmentation using Adversarial Networks

Pauline Luc, Camille Couprie, Soumith Chintala, Jakob Verbeek

BMVC - September 18, 2016

A MultiPath Network for Object Detection

Sergey Zagoruyko, Adam Lerer, Tsung-Yi Lin, Pedro O. Pinheiro, Sam Gross, Soumith Chintala, Piotr Dollár

ArXiv - November 23, 2015

MazeBase: A Sandbox for Learning from Games

Sainbayar Sukhbaatar, Arthur Szlam, Gabriel Synnaeve, Soumith Chintala, Rob Fergus

ArXiv - June 25, 2015

Scale-Invariant Learning and Convolutional Networks

Mark Tygert, Arthur Szlam, Soumith Chintala, Marc'Aurelio Ranzato, Yuandong Tian, Wojciech Zaremba

June 22, 2015

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun

ArXiv - June 22, 2015

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

Emily Denton, Soumith Chintala, Arthur Szlam, Rob Fergus

ArXiv - June 22, 2015

A Theoretical Argument for Complex-Valued Convolutional Networks

Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert

HPCA 2018 - February 24, 2018

Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective

Kim Hazelwood, Sarah Bird, David Brooks, Soumith Chintala, Utku Diril, Dmytro Dzhulgakov, Mohamed Fawzy, Bill Jia, Yangqing Jia, Aditya Kalro, James Law, Kevin Lee, Jason Lu, Pieter Noordhuis, Misha Smelyanskiy, Liang Xiong, Xiaodong Wang