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07/27/2022
Atomic structure generation from reconstructing structural fingerprints
Data-driven machine learning methods have the potential to dramatically ...
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07/25/2022
Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks
We propose a stable, parallel approach to train Wasserstein Conditional ...
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10/26/2021
Stable Anderson Acceleration for Deep Learning
Anderson acceleration (AA) is an extrapolation technique designed to spe...
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10/21/2021
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems
Scientific communities are increasingly adopting machine learning and de...
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09/12/2021
Neural network based order parameter for phase transitions and its applications in high-entropy alloys
Phase transition is one of the most important phenomena in nature and pl...
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02/21/2021
Scalable Balanced Training of Conditional Generative Adversarial Neural Networks on Image Data
We propose a distributed approach to train deep convolutional generative...
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12/16/2020
Data optimization for large batch distributed training of deep neural networks
Distributed training in deep learning (DL) is common practice as data an...
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12/03/2020
Distributed Training and Optimization Of Neural Networks
Deep learning models are yielding increasingly better performances thank...
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11/23/2020
Integrating Deep Learning in Domain Sciences at Exascale
This paper presents some of the current challenges in designing deep lea...
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10/13/2020
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
The drug discovery process currently employed in the pharmaceutical indu...
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09/24/2019
Exascale Deep Learning for Scientific Inverse Problems
We introduce novel communication strategies in synchronous distributed D...
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09/07/2019
A greedy constructive algorithm for the optimization of neural network architectures
In this work we propose a new method to optimize the architecture of an ...
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08/10/2019
Robust data-driven approach for predicting the configurational energy of high entropy alloys
High entropy alloys (HEAs) have been increasingly attractive as promisin...
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11/06/2018