Research Areas

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At Facebook, research permeates everything we do. We believe the most interesting research questions are derived from real world problems. Working on cutting edge research with a practical focus, we push product boundaries every day. At the same time, we publish papers, give talks, and collaborate broadly with the academic community.

We solve real-world problems that impact billions of people in areas such as:

Latest Publications

All Publications

ICPR - January 15, 2021

Meta Learning via Learned Loss

Sarah Bechtle, Artem Molchanov, Yevgen Chebotar, Edward Grefenstette, Ludovic Righetti, Gaurav S. Sukhatme, Franziska Meier

IJCAI - January 5, 2021

IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL

Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam

IEEE Transactions on Automatic Control - January 1, 2021

Asynchronous Gradient-Push

Mahmoud Assran, Michael Rabbat

SPCE - December 21, 2020

Contact Burn Injuries Part I: The influence of object thermal mass

May Yen, Francesco Colella, Harri Kytomaa, Boyd Allin, Alex Ockfen

SPCE - December 21, 2020

Contact Burn Injuries Part II: The influence of object shape, size, contact resistance, and applied heat flux

May Yen, Francesco Colella, Harri Kytomaa, Boyd Allin, Alex Ockfen

NeurIPS - December 16, 2020

Online Bayesian Persuasion

Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti

NeurIPS - December 15, 2020

Triple descent and the two kinds of overfitting: Where & why do they appear?

St├ęphane d'Ascoli, Levent Sagun, Giulio Biroli

COLING - December 8, 2020

Situated and Interactive Multimodal Conversations

Seungwhan Moon, Satwik Kottur, Paul A. Crook, Ankita De, Shivani Poddar, Theodore Levin, David Whitney, Daniel Difranco, Ahmad Beirami, Eunjoon Cho, Rajen Subba, Alborz Geramifard

Downloads & Projects

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PyTorch is a Python package that provides two high-level features: tensor computation (like NumPy) with strong GPU acceleration and deep neural networks built on a tape-based autograd system.

Dense human pose estimation aims at mapping all human pixels of an RGB image to the 3D surface of the human body.

Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

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