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Romain Egele
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Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles


Feb 20, 2023
Romit Maulik, Romain Egele, Krishnan Raghavan, Prasanna Balaprakash

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HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization


Oct 03, 2022
Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy, Srinivasan Ramesh, Allen D. Malony, Rob Ross

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* Accepted at IEEE Cluster 2022 
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Asynchronous Distributed Bayesian Optimization at HPC Scale


Jul 04, 2022
Romain Egele, Joceran Gouneau, Venkatram Vishwanath, Isabelle Guyon, Prasanna Balaprakash

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AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification


Oct 26, 2021
Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch

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AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data


Oct 30, 2020
Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon, Zhengying Liu

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Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research


Sep 01, 2019
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens

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* SC '19: IEEE/ACM International Conference on High Performance Computing, Networking, Storage and Analysis, November 17--22, 2019, Denver, CO 
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