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Journal Articles
- 2024
[j1]N. T. Hunt-Smith
, W. Melnitchouk, F. Ringer, Nobuo Sato, A. W. Thomas, M. J. White:
Accelerating Markov Chain Monte Carlo sampling with diffusion models. Comput. Phys. Commun. 296: 109059 (2024)
Conference and Workshop Papers
- 2022
- [c5]Manal Almaeen, Yasir Alanazi, Nobuo Sato, W. Melnitchouk, Yaohang Li:
Point Cloud-based Variational Autoencoder Inverse Mappers (PC-VAIM) - An Application on Quantum Chromodynamics Global Analysis. ICMLA 2022: 1151-1158 - 2021
- [c4]Yasir Alanazi, Nobuo Sato, Tianbo Liu, Wally Melnitchouk, Pawel Ambrozewicz, Florian Hauenstein, Michelle P. Kuchera, Evan Pritchard, Michael Robertson, Ryan R. Strauss, Luisa Velasco, Yaohang Li:
Simulation of Electron-Proton Scattering Events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN). IJCAI 2021: 2126-2132 - [c3]Yasir Alanazi, Nobuo Sato, Pawel Ambrozewicz, Astrid N. Hiller Blin, Wally Melnitchouk, Marco Battaglieri, Tianbo Liu, Yaohang Li:
A Survey of Machine Learning-Based Physics Event Generation. IJCAI 2021: 4286-4293 - [c2]Manal Almaeen, Yasir Alanazi, Nobuo Sato, W. Melnitchouk, Michelle P. Kuchera, Yaohang Li:
Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems. IJCNN 2021: 1-8 - 2020
- [c1]Luisa Velasco, Evan McClellan, Nobuo Sato, Pawel Ambrozewicz, Tianbo Liu, W. Melnitchouk, Michelle P. Kuchera, Yasir Alanazi, Yaohang Li:
cFAT-GAN: Conditional Simulation of Electron-Proton Scattering Events with Variate Beam Energies by a Feature Augmented and Transformed Generative Adversarial Network. ICMLA 2020: 372-375
Informal and Other Publications
- 2021
- [i2]Yasir Alanazi, Nobuo Sato, Pawel Ambrozewicz, Astrid N. Hiller Blin, W. Melnitchouk, Marco Battaglieri, Tianbo Liu, Yaohang Li:
A survey of machine learning-based physics event generation. CoRR abs/2106.00643 (2021) - 2020
- [i1]Yasir Alanazi, Nobuo Sato, Tianbo Liu, W. Melnitchouk, Michelle P. Kuchera, Evan Pritchard, Michael Robertson, Ryan R. Strauss, Luisa Velasco, Yaohang Li:
Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN). CoRR abs/2001.11103 (2020)
Coauthor Index
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