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ORCIDMichelle P. Kuchera
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2020 – today
- 2022
[j1]Braden Kronheim
, Michelle P. Kuchera, Harrison B. Prosper:
TensorBNN: Bayesian inference for neural networks using TensorFlow. Comput. Phys. Commun. 270: 108168 (2022)- [i8]Cade Dembski, Michelle P. Kuchera, Sean Liddick, Raghu Ramanujan, Artemis Spyrou:
Two-dimensional total absorption spectroscopy with conditional generative adversarial networks. CoRR abs/2206.11792 (2022) - 2021
- [c3]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 - [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 - [i7]Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Raghuram Ramanujan:
Implicit Quantile Neural Networks for Jet Simulation and Correction. CoRR abs/2111.11415 (2021) - [i6]Amber Boehnlein, Markus Diefenthaler, Cristiano Fanelli, Morten Hjorth-Jensen, Tanja Horn, Michelle P. Kuchera, Dean Lee, Witold Nazarewicz, Kostas Orginos, Peter Ostroumov, Long-Gang Pang, Alan Poon, Nobuo Sato, Malachi Schram, Alexander Scheinker, Michael S. Smith, Xin-Nian Wang, Veronique Ziegler:
Artificial Intelligence and Machine Learning in Nuclear Physics. CoRR abs/2112.02309 (2021) - 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 - [i5]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) - [i4]Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Alexander Karbo:
Bayesian Neural Networks for Fast SUSY Predictions. CoRR abs/2007.04506 (2020) - [i3]Robert Solli, Daniel Bazin, Michelle P. Kuchera, Ryan R. Strauss, Morten Hjorth-Jensen:
Unsupervised Learning for Identifying Events in Active Target Experiments. CoRR abs/2008.02757 (2020) - [i2]Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper:
TensorBNN: Bayesian Inference for Neural Networks using Tensorflow. CoRR abs/2009.14393 (2020)
2010 – 2019
- 2018
- [i1]Michelle P. Kuchera, Raghuram Ramanujan, Jack Z. Taylor, Ryan R. Strauss, Daniel Bazin, Joshua Bradt, Ruiming Chen:
Machine Learning Methods for Track Classification in the AT-TPC. CoRR abs/1810.10350 (2018)
Coauthor Index
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