Anuroop Sriram | DeepAI

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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...

11 C. Lawrence Zitnick, et al. ∙

∙ 06/27/2022

Wav2Vec-Aug: Improved self-supervised training with limited data

Self-supervised learning (SSL) of speech representations has received mu...

0 Anuroop Sriram, et al. ∙

∙ 06/17/2022

The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis

Computational catalysis and machine learning communities have made consi...

31 Richard Tran, et al. ∙

∙ 04/06/2022

How Do Graph Networks Generalize to Large and Diverse Molecular Systems?

The predominant method of demonstrating progress of atomic graph neural ...

78 Johannes Gasteiger, et al. ∙

∙ 03/18/2022

Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations

Recent progress in Graph Neural Networks (GNNs) for modeling atomic simu...

7 Anuroop Sriram, et al. ∙

∙ 06/17/2021

Rotation Invariant Graph Neural Networks using Spin Convolutions

Progress towards the energy breakthroughs needed to combat climate chang...

46 Muhammed Shuaibi, et al. ∙

∙ 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...

0 Wei-Ning Hsu, et al. ∙

∙ 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...

54 Weihua Hu, et al. ∙

∙ 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...

12 Anuroop Sriram, et al. ∙

∙ 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...

0 Matthew J. Muckley, et al. ∙

∙ 12/07/2020

MLS: A Large-Scale Multilingual Dataset for Speech Research

This paper introduces Multilingual LibriSpeech (MLS) dataset, a large mu...

0 Vineel Pratap, et al. ∙

∙ 10/20/2020

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

Catalyst discovery and optimization is key to solving many societal and ...

38 Lowik Chanussot, et al. ∙

∙ 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...

17 C. Lawrence Zitnick, et al. ∙

∙ 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...

0 Vineel Pratap, et al. ∙

∙ 04/14/2020

End-to-End Variational Networks for Accelerated MRI Reconstruction

The slow acquisition speed of magnetic resonance imaging (MRI) has led t...

5 Anuroop Sriram, et al. ∙

∙ 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...

74 Florian Knoll, et al. ∙

∙ 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 ...

0 Gabriel Synnaeve, et al. ∙

∙ 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...

0 Mahaveer Jain, et al. ∙

∙ 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...

23 Anuroop Sriram, et al. ∙

∙ 11/21/2018

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measuremen...

21 Jure Žbontar, et al. ∙

∙ 11/05/2017

Robust Speech Recognition Using Generative Adversarial Networks

This paper describes a general, scalable, end-to-end framework that uses...

0 Anuroop Sriram, et al. ∙

∙ 08/21/2017

Cold Fusion: Training Seq2Seq Models Together with Language Models

Sequence-to-sequence (Seq2Seq) models with attention have excelled at ta...

0 Anuroop Sriram, et al. ∙

∙ 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...

0 Eric Battenberg, et al. ∙

∙ 05/11/2017

Reducing Bias in Production Speech Models

Replacing hand-engineered pipelines with end-to-end deep learning system...

0 Eric Battenberg, et al. ∙

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