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Romain Egele
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2020 – today
- 2024
- [j2]Xin Liu, Mario Rüttgers, Alessio Quercia, Romain Egele, Elisabeth Pfaehler, Rushikesh Shende, Marcel Aach, Wolfgang Schröder, Prasanna Balaprakash, Andreas Lintermann:
Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations. Future Gener. Comput. Syst. 159: 474-488 (2024) - [j1]Romain Egele
, Felix Mohr
, Tom J. Viering
, Prasanna Balaprakash:
The unreasonable effectiveness of early discarding after one epoch in neural network hyperparameter optimization. Neurocomputing 597: 127964 (2024) - [i12]Romain Egele, Felix Mohr, Tom J. Viering, Prasanna Balaprakash:
The Unreasonable Effectiveness Of Early Discarding After One Epoch In Neural Network Hyperparameter Optimization. CoRR abs/2404.04111 (2024) - [i11]Yixuan Sun
, Olaperi Yeside Sowunmi, Romain Egele, Sri Hari Krishna Narayanan, Luke Van Roekel, Prasanna Balaprakash:
Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach. CoRR abs/2404.05768 (2024) - [i10]Romain Egele, Júlio C. S. Jacques Júnior, Jan N. van Rijn, Isabelle Guyon, Xavier Baró, Albert Clapés, Prasanna Balaprakash, Sergio Escalera, Thomas B. Moeslund, Jun Wan:
AI Competitions and Benchmarks: Dataset Development. CoRR abs/2404.09703 (2024) - 2023
- [c7]Romain Égelé
, Isabelle Guyon, Venkatram Vishwanath, Prasanna Balaprakash:
Asynchronous Decentralized Bayesian Optimization for Large Scale Hyperparameter Optimization. e-Science 2023: 1-10 - [c6]Romain Egele, Isabelle Guyon, Yixuan Sun, Prasanna Balaprakash:
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization? ESANN 2023 - [i9]Romit Maulik, Romain Egele, Krishnan Raghavan, Prasanna Balaprakash:
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles. CoRR abs/2302.09748 (2023) - [i8]Romain Egele, Isabelle Guyon, Yixuan Sun, Prasanna Balaprakash:
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization? CoRR abs/2307.15422 (2023) - [i7]Romain Egele, Tyler Chang, Yixuan Sun, Venkatram Vishwanath, Prasanna Balaprakash:
Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives. CoRR abs/2309.14936 (2023) - [i6]Sajal Dash, Isaac Lyngaas, Junqi Yin
, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash:
Optimizing Distributed Training on Frontier for Large Language Models. CoRR abs/2312.12705 (2023) - 2022
- [c5]Matthieu Dorier
, Romain Egele
, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy
, Srinivasan Ramesh, Allen D. Malony, Robert B. Ross:
HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization. CLUSTER 2022: 381-393 - [c4]Romain Egele, Romit Maulik, Krishnan Raghavan, Bethany Lusch, Isabelle Guyon, Prasanna Balaprakash:
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. ICPR 2022: 1908-1914 - [i5]Romain Egele, Joceran Gouneau, Venkatram Vishwanath, Isabelle Guyon, Prasanna Balaprakash:
Asynchronous Distributed Bayesian Optimization at HPC Scale. CoRR abs/2207.00479 (2022) - [i4]Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy
, Srinivasan Ramesh, Allen D. Malony, Robert B. Ross:
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization. CoRR abs/2210.00798 (2022) - 2021
- [c3]Romain Égelé
, Prasanna Balaprakash
, Isabelle Guyon, Venkatram Vishwanath, Fangfang Xia, Rick Stevens, Zhengying Liu:
AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. SC 2021: 30 - [i3]Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch:
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. CoRR abs/2110.13511 (2021) - 2020
- [c2]Romit Maulik
, Romain Egele
, Bethany Lusch
, Prasanna Balaprakash:
Recurrent neural network architecture search for geophysical emulation. SC 2020: 8 - [i2]Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon, Zhengying Liu:
AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data. CoRR abs/2010.16358 (2020)
2010 – 2019
- 2019
- [c1]Prasanna Balaprakash, Romain Egele
, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens:
Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. SC 2019: 37:1-37:33 - [i1]Prasanna Balaprakash, Romain Egele
, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens:
Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research. CoRR abs/1909.00311 (2019)
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last updated on 2024-08-06 22:02 CEST by the dblp team
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