Michelle P. Kuchera

Publication Activity (10 Years)

Years Active: 2018-2022
Publications (10 Years): 12

Top Topics

Top Venues

Comput. Phys. Commun.

Publications

Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper
TensorBNN: Bayesian inference for neural networks using TensorFlow. Comput. Phys. Commun. 270 (2022)
Cade Dembski, Michelle P. Kuchera, Sean Liddick, Raghu Ramanujan, Artemis Spyrou
Two-dimensional total absorption spectroscopy with conditional generative adversarial networks. CoRR (2022)
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)
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 (2021)
Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Raghuram Ramanujan
Implicit Quantile Neural Networks for Jet Simulation and Correction. CoRR (2021)
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)
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)
Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Alexander Karbo
Bayesian Neural Networks for Fast SUSY Predictions. CoRR (2020)
Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper
TensorBNN: Bayesian Inference for Neural Networks using Tensorflow. CoRR (2020)
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 (2020)
Robert Solli, Daniel Bazin, Michelle P. Kuchera, Ryan R. Strauss, Morten Hjorth-Jensen
Unsupervised Learning for Identifying Events in Active Target Experiments. CoRR (2020)
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 (2018)