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06/29/2022
Spherical Channels for Modeling Atomic Interactions
Modeling the energy and forces of atomic systems is a fundamental proble...
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06/27/2022
Wav2Vec-Aug: Improved self-supervised training with limited data
Self-supervised learning (SSL) of speech representations has received mu...
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06/17/2022
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis
Computational catalysis and machine learning communities have made consi...
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04/06/2022
How Do Graph Networks Generalize to Large and Diverse Molecular Systems?
The predominant method of demonstrating progress of atomic graph neural ...
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03/18/2022
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
Recent progress in Graph Neural Networks (GNNs) for modeling atomic simu...
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06/17/2021
Rotation Invariant Graph Neural Networks using Spin Convolutions
Progress towards the energy breakthroughs needed to combat climate chang...
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04/02/2021
Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Training
Self-supervised learning of speech representations has been a very activ...
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03/02/2021
ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations
With massive amounts of atomic simulation data available, there is a hug...
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01/13/2021
COVID-19 Deterioration Prediction via Self-Supervised Representation Learning and Multi-Image Prediction
The rapid spread of COVID-19 cases in recent months has strained hospita...
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12/09/2020
State-of-the-art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge
Accelerating MRI scans is one of the principal outstanding problems in t...
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12/07/2020
MLS: A Large-Scale Multilingual Dataset for Speech Research
This paper introduces Multilingual LibriSpeech (MLS) dataset, a large mu...
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10/20/2020
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
Catalyst discovery and optimization is key to solving many societal and ...
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10/14/2020
An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage
Scalable and cost-effective solutions to renewable energy storage are es...
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07/06/2020
Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters
We study training a single acoustic model for multiple languages with th...
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04/14/2020
End-to-End Variational Networks for Accelerated MRI Reconstruction
The slow acquisition speed of magnetic resonance imaging (MRI) has led t...
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01/06/2020
Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge
Purpose: To advance research in the field of machine learning for MR ima...
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11/19/2019
End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
We study ResNet-, Time-Depth Separable ConvNets-, and Transformer-based ...
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11/05/2019
RNN-T For Latency Controlled ASR With Improved Beam Search
Neural transducer-based systems such as RNN Transducers (RNN-T) for auto...
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10/27/2019
GrappaNet: Combining Parallel Imaging with Deep Learning for Multi-Coil MRI Reconstruction
Magnetic Resonance Image (MRI) acquisition is an inherently slow process...
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11/21/2018
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measuremen...
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11/05/2017
Robust Speech Recognition Using Generative Adversarial Networks
This paper describes a general, scalable, end-to-end framework that uses...
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08/21/2017
Cold Fusion: Training Seq2Seq Models Together with Language Models
Sequence-to-sequence (Seq2Seq) models with attention have excelled at ta...
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07/24/2017
Exploring Neural Transducers for End-to-End Speech Recognition
In this work, we perform an empirical comparison among the CTC, RNN-Tran...
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05/11/2017