b'Facebook'

research

∙ 12/03/2019

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

Deep learning frameworks have often focused on either usability or speed...

Adam Paszke, et al. ∙

research

∙ 06/21/2020

Feel The Music: Automatically Generating A Dance For An Input Song

We present a general computational approach that enables a machine to ge...

Purva Tendulkar, et al. ∙

research

∙ 06/25/2019

Learning Causal State Representations of Partially Observable Environments

Intelligent agents can cope with sensory-rich environments by learning t...

Amy Zhang, et al. ∙

research

∙ 04/22/2022

End-to-end symbolic regression with transformers

Symbolic regression, the task of predicting the mathematical expression ...

Pierre-Alexandre Kamienny, et al. ∙

research

∙ 03/03/2022

Understanding Failure Modes of Self-Supervised Learning

Self-supervised learning methods have shown impressive results in downst...

Neha Mukund Kalibhat, et al. ∙

research

∙ 06/10/2019

A Survey of Reinforcement Learning Informed by Natural Language

To be successful in real-world tasks, Reinforcement Learning (RL) needs ...

Jelena Luketina, et al. ∙

research

∙ 04/28/2020

Streamlining Tensor and Network Pruning in PyTorch

In order to contrast the explosion in size of state-of-the-art machine l...

Michela Paganini, et al. ∙

research

∙ 12/20/2018

nocaps: novel object captioning at scale

Image captioning models have achieved impressive results on datasets con...

Harsh Agrawal, et al. ∙

research

∙ 05/03/2021

Neural Monocular 3D Human Motion Capture with Physical Awareness

We present a new trainable system for physically plausible markerless 3D...

Soshi Shimada, et al. ∙

research

∙ 09/09/2019

Exploratory Combinatorial Optimization with Reinforcement Learning

Many real-world problems can be reduced to combinatorial optimization on...

Thomas D. Barrett, et al. ∙

research

∙ 10/02/2018

Learning with Random Learning Rates

Hyperparameter tuning is a bothersome step in the training of deep learn...

Léonard Blier, et al. ∙

research

∙ 04/12/2021

Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models

Deep learning recommendation models (DLRMs) are used across many busines...

Dheevatsa Mudigere, et al. ∙

research

∙ 04/25/2019

Holistic Large Scale Video Understanding

Action recognition has been advanced in recent years by benchmarks with ...

Ali Diba, et al. ∙

research

∙ 04/15/2020

Training with Quantization Noise for Extreme Model Compression

We tackle the problem of producing compact models, maximizing their accu...

Angela Fan, et al. ∙

research

∙ 11/20/2019

Generating Interactive Worlds with Text

Procedurally generating cohesive and interesting game environments is ch...

Angela Fan, et al. ∙

research

∙ 04/23/2019

Monte-Carlo Tree Search for Efficient Visually Guided Rearrangement Planning

In this paper, we address the problem of visually guided rearrangement p...

Sergey Zagoruyko, et al. ∙

research

∙ 09/10/2019

Bayesian Relational Memory for Semantic Visual Navigation

We introduce a new memory architecture, Bayesian Relational Memory (BRM)...

Yi Wu, et al. ∙

research

∙ 10/18/2021

Learning in High Dimension Always Amounts to Extrapolation

The notion of interpolation and extrapolation is fundamental in various ...

Randall Balestriero, et al. ∙

research

∙ 11/28/2019

Self-Supervised Learning by Cross-Modal Audio-Video Clustering

The visual and audio modalities are highly correlated yet they contain d...

Humam Alwassel, et al. ∙

research

∙ 03/04/2021

DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks

The recent research explosion around implicit neural representations, su...

Thomas Neff, et al. ∙

research

∙ 01/08/2020

Convolutional Networks with Dense Connectivity

Recent work has shown that convolutional networks can be substantially d...

Gao Huang, et al. ∙

research

∙ 09/30/2019

Single-Network Whole-Body Pose Estimation

We present the first single-network approach for 2D whole-body pose esti...

Gines Hidalgo, et al. ∙

research

∙ 06/05/2020

Visual Transformers: Token-based Image Representation and Processing for Computer Vision

Computer vision has achieved great success using standardized image repr...

Bichen Wu, et al. ∙

research

∙ 11/14/2019

Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA

Many visual scenes contain text that carries crucial information, and it...

Ronghang Hu, et al. ∙

research

∙ 06/22/2020

Learning with AMIGo: Adversarially Motivated Intrinsic Goals

A key challenge for reinforcement learning (RL) consists of learning in ...

Andres Campero, et al. ∙

research

∙ 09/06/2021

Detecting Inspiring Content on Social Media

Inspiration moves a person to see new possibilities and transforms the w...

Oana Ignat, et al. ∙

research

∙ 01/25/2019

Emergent Linguistic Phenomena in Multi-Agent Communication Games

In this work, we propose a computational framework in which agents equip...

Laura Graesser, et al. ∙

research

∙ 12/05/2021

Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning

Continual learning (CL) learns a sequence of tasks incrementally with th...

Zixuan Ke, et al. ∙

research

∙ 09/06/2019

Supervised Multimodal Bitransformers for Classifying Images and Text

Self-supervised bidirectional transformer models such as BERT have led t...

Douwe Kiela, et al. ∙

research

∙ 06/22/2020

Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions

We present our view of what is necessary to build an engaging open-domai...

Stephen Roller, et al. ∙

research

∙ 11/19/2019

Live Face De-Identification in Video

We propose a method for face de-identification that enables fully automa...

Oran Gafni, et al. ∙

research

∙ 07/24/2019

Unsupervised Discovery of Decision States for Transfer in Reinforcement Learning

We present a hierarchical reinforcement learning (HRL) or options framew...

Nirbhay Modhe, et al. ∙

research

∙ 06/08/2020

Linformer: Self-Attention with Linear Complexity

Large transformer models have shown extraordinary success in achieving s...

Sinong Wang, et al. ∙

research

∙ 09/08/2021

What's Hidden in a One-layer Randomly Weighted Transformer?

We demonstrate that, hidden within one-layer randomly weighted neural ne...

Sheng Shen, et al. ∙

research

∙ 09/17/2021

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

Interest in applying Artificial Intelligence (AI) techniques to compiler...

Chris Cummins, et al. ∙

research

∙ 08/08/2018

Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance

Individual neurons in convolutional neural networks supervised for image...

Ramprasaath R. Selvaraju, et al. ∙

research

∙ 01/31/2020

Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization

Bayesian optimization (BO) is a popular approach to optimize expensive-t...

Benjamin Letham, et al. ∙

research

∙ 12/15/2020

TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors

Simulators perform an important role in prototyping, debugging and bench...

Shaoxiong Wang, et al. ∙

research

∙ 07/09/2021

EasyCom: An Augmented Reality Dataset to Support Algorithms for Easy Communication in Noisy Environments

Augmented Reality (AR) as a platform has the potential to facilitate the...

Jacob Donley, et al. ∙

research

∙ 11/03/2021

What Robot do I Need? Fast Co-Adaptation of Morphology and Control using Graph Neural Networks

The co-adaptation of robot morphology and behaviour becomes increasingly...

Kevin Sebastian Luck, et al. ∙

research

∙ 02/01/2022

WebFormer: The Web-page Transformer for Structure Information Extraction

Structure information extraction refers to the task of extracting struct...

Qifan Wang, et al. ∙

research

∙ 02/18/2021

Unbiased Teacher for Semi-Supervised Object Detection

Semi-supervised learning, i.e., training networks with both labeled and ...

Yen-Cheng Liu, et al. ∙

research

∙ 12/16/2021

Learning Bounded Context-Free-Grammar via LSTM and the Transformer:Difference and Explanations

Long Short-Term Memory (LSTM) and Transformers are two popular neural ar...

Hui Shi, et al. ∙

research

∙ 07/16/2022

CHARM: A Hierarchical Deep Learning Model for Classification of Complex Human Activities Using Motion Sensors

In this paper, we report a hierarchical deep learning model for classifi...

Eric Rosen, et al. ∙

research

∙ 06/05/2018

Learning to Follow Language Instructions with Adversarial Reward Induction

Recent work has shown that deep reinforcement-learning agents can learn ...

Dzmitry Bahdanau, et al. ∙

research

∙ 07/09/2018

Talk the Walk: Navigating New York City through Grounded Dialogue

We introduce "Talk The Walk", the first large-scale dialogue dataset gro...

Harm de Vries, et al. ∙

research

∙ 12/11/2018

2.5D Visual Sound

Binaural audio provides a listener with 3D sound sensation, allowing a r...

Ruohan Gao, et al. ∙

research

∙ 02/15/2019

Cycle-Consistency for Robust Visual Question Answering

Despite significant progress in Visual Question Answering over the years...

Meet Shah, et al. ∙

research

∙ 04/02/2019

Analysing Mathematical Reasoning Abilities of Neural Models

Mathematical reasoning---a core ability within human intelligence---pres...

David Saxton, et al. ∙

research

∙ 05/03/2019

Data-efficient Learning of Morphology and Controller for a Microrobot

Robot design is often a slow and difficult process requiring the iterati...

Thomas Liao, et al. ∙

Facebook

Featured Researchers