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ORCIDMichelle P. Kuchera
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2020 – today
- 2025
[i11]Mingyang Li, Michelle P. Kuchera, Raghuram Ramanujan, Adam Anthony, Curtis Hunt, Yassid Ayyad
:
Unpaired Translation of Point Clouds for Modeling Detector Response. CoRR abs/2501.18674 (2025)- [i10]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 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:
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR abs/2509.02661 (2025) - [i9]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:
Sparse Methods for Vector Embeddings of TPC Data. CoRR abs/2511.11221 (2025) - 2024
- [j2]Braden Kronheim, Ali Al Kadhim, Michelle P. Kuchera, Harrison B. Prosper, Raghuram Ramanujan:
Implicit quantile networks for emulation in jet physics. Mach. Learn. Sci. Technol. 5(3): 45073 (2024) - 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, Wally 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 W. P. 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, Wally 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, Wally 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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