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RESEARCH
NLP
The evolution of deep learning and PyTorch
March 09, 2020
AR/VR
ML APPLICATIONS
Using integrated ML to deliver low-latency mobile VR graphics
March 05, 2020
COMPUTER VISION
ML APPLICATIONS
Powered by AI: Turning any 2D photo into 3D using convolutional neural nets
February 28, 2020
Open-Source AI Tools
We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.
Open-Source AI Research
We're advancing the state-of-the-art in artificial intelligence through fundamental and applied research in open collaboration with the community.
Notable Papers
COMPUTER VISION
Live Face De-Identification in Video
Oran Gafni
Lior Wolf
Yaniv Taigman
International Conference on Computer Vision (ICCV)
RESEARCH
COMPUTER VISION
TensorMask: A Foundation for Dense Object Segmentation
Xinlei Chen
Ross Girshick
Kaiming He
Piotr Dollar
International Conference on Computer Vision (ICCV)
RESEARCH
Single-Network Whole-Body Pose Estimation
Gines Hidalgo
Yaadhav Raaj
Haroon Idrees
Donglai Xiang...
International Conference on Computer Vision (ICCV)
COMPUTER VISION
A Universal Music Translation Network
Noam Mor
Lior Wolf
Adam Polyak
Yaniv Taigman
International Conference on Learning Representations (ICLR)
Latest Publications
April 27, 2020
RESEARCH
The Early Phase of Neural Network Training
Recent studies have shown that many important aspects of neural network learning take place within the very earliest iterations or epochs of training. For example, sparse, trainable sub-networks emerge (Frankle et al., 2019), gradient descent…
Jonathan Frankle, David J. Schwab, Ari Morcos
April 27, 2020
April 26, 2020
RESEARCH
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
Distributed optimization is essential for training large models on large datasets. Multiple approaches have been proposed to reduce the communication overhead in distributed training, such as synchronizing only after performing multiple local…
Jianyu Wang, Vinayak Tantia, Nicolas Ballas, Michael Rabbat
April 26, 2020
April 25, 2020
RESEARCH
And the bit goes down: Revisiting the quantization of neural networks
In this paper, we address the problem of reducing the memory footprint of convolutional network architectures. We introduce a vector quantization method that aims at preserving the quality of the reconstruction of the network outputs rather…
Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou
April 25, 2020
April 25, 2020
RESEARCH
Permutation Equivariant Models for Compositional Generalization in Language
Humans understand novel sentences by composing meanings and roles of core language components. In contrast, neural network models for natural language modeling fail when such compositional generalization is required. The main contribution of…
Jonathan Gordon, David Lopez-Paz, Marco Baroni, Diane Bouchacourt
April 25, 2020
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We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.
