Michelle P. Kuchera

According to our database, Michelle P. Kuchera authored at least 11 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

TensorBNN: Bayesian inference for neural networks using TensorFlow.

Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper

Comput. Phys. Commun., 2022

Two-dimensional total absorption spectroscopy with conditional generative adversarial networks.

Cade Dembski, Michelle P. Kuchera, Sean Liddick, Raghu Ramanujan, Artemis Spyrou

CoRR, 2022

2021

Artificial Intelligence and Machine Learning in Nuclear Physics.

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

CoRR, 2021

Implicit Quantile Neural Networks for Jet Simulation and Correction.

Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Raghuram Ramanujan

CoRR, 2021

Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems.

Manal Almaeen, Yasir Alanazi, Nobuo Sato, W. Melnitchouk, Michelle P. Kuchera, Yaohang Li

Proceedings of the International Joint Conference on Neural Networks, 2021

Simulation of Electron-Proton Scattering Events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN).

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

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020

Unsupervised Learning for Identifying Events in Active Target Experiments.

Robert Solli, Daniel Bazin, Michelle P. Kuchera, Ryan R. Strauss, Morten Hjorth-Jensen

CoRR, 2020

Bayesian Neural Networks for Fast SUSY Predictions.

Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Alexander Karbo

CoRR, 2020

Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN).

Yasir Alanazi, Nobuo Sato, Tianbo Liu, W. Melnitchouk, Michelle P. Kuchera, Evan Pritchard, Michael Robertson, Ryan R. Strauss, Luisa Velasco, Yaohang Li

CoRR, 2020

cFAT-GAN: Conditional Simulation of Electron-Proton Scattering Events with Variate Beam Energies by a Feature Augmented and Transformed Generative Adversarial Network.

Luisa Velasco, Evan McClellan, Nobuo Sato, Pawel Ambrozewicz, Tianbo Liu, W. Melnitchouk, Michelle P. Kuchera, Yasir Alanazi, Yaohang Li

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2018

Machine Learning Methods for Track Classification in the AT-TPC.

Michelle P. Kuchera, Raghuram Ramanujan, Jack Z. Taylor, Ryan R. Strauss, Daniel Bazin, Joshua Bradt, Ruiming Chen

CoRR, 2018