Michelle P. Kuchera

According to our database, Michelle P. Kuchera authored at least 15 papers between 2018 and 2025.

Collaborative distances:

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

2025

Sparse Methods for Vector Embeddings of TPC Data.

Tyler Wheeler, Michelle P. Kuchera, Raghuram Ramanujan, Ryan Krupp, Chris Wrede, Saiprasad Ravishankar, Connor L. Cross, Hoi Yan Ian Heung, Andrew J. Jones, Benjamin Votaw

CoRR, November, 2025

The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS).

Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella S. R. Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang

CoRR, September, 2025

Unpaired Translation of Point Clouds for Modeling Detector Response.

Mingyang Li, Michelle P. Kuchera, Raghuram Ramanujan, Adam Anthony, Curtis Hunt, Yassid Ayyad

CoRR, January, 2025

2024

Implicit quantile networks for emulation in jet physics.

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

Mach. Learn. Sci. Technol., 2024

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 W. P. 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, Wally 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, Wally 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, Wally 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