ALPhA members are bold in the author lists below.

Two-dimensional total absorption spectroscopy with conditional generative adversarial networks

C. Dembski, M.P. Kuchera, S. Liddick, R. Ramanujan, A. Spyrou

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Volume 1060, 2024

DOI: https://doi.org/10.1016/j.nima.2023.169026

URL: https://www.sciencedirect.com/science/article/pii/S0168900223010264?dgcid=coauthor

Machine learning-based event generator for electron-proton scattering

Y. Alanazi, P. Ambrozewicz, M. Battaglieri, A. N. Hiller Blin, M. P. Kuchera, Y. Li, T. Liu, R. E. McClellan, W. Melnitchouk, E. Pritchard, M. Robertson, N. Sato, R. Strauss, and L. Velasco

Physical Review D, 106, 096002, 2022

URL: https://journals.aps.org/prd/abstract/10.1103/PhysRevD.106.096002

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

Reviews of Modern Physics, 94, 031003, 2022

URL: https://arxiv.org/pdf/2112.02309.pdf

Implicit Quantile Neural Networks for Jet Simulation and Correction

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

NeurIPS Machine Learning and the Physical Sciences workshop, 2021

URL: https://arxiv.org/pdf/2111.11415.pdf

Conditional Wasserstein Generative Adversarial Networks for Fast Detector Simulation

John Blue, Braden Kronheim, Michelle Kuchera, and Raghuram Ramanujan

25th International Conference on Computing in High Energy and Nuclear Physics (CHEP). Computational European Physical Journal (EPJ) Web of Conferences, 251, 03055, 2021

DOI: https://doi.org/10.1051/epjconf/202125103055

URL: https://www.epj-conferences.org/articles/epjconf/pdf/2021/05/epjconf_chep2021_03055.pdf

TensorBNN: Bayesian Inference for Neural Networks using Tensorflow

B. Kronheim, M.P. Kuchera, H.B. Prosper

Computer Physics Communications, 270, 108168, 2022

DOI: https://doi.org/10.1016/j.cpc.2021.108168

URL: https://arxiv.org/abs/2009.14393

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

Y. Alanazi, N. Sato, T. Liu, W. Melnitchouk, M. P. Kuchera, E. Pritchard, M. Robertson, R.R. Strauss, L. Velasco, Y. Li

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

DOI: https://doi.org/10.24963/ijcai.2021/293

URL: https://www.ijcai.org/proceedings/2021/293

Unsupervised Learning for Identifying Events in Active Target Experiments

R. Solli, D. Bazin, Morten Hjorth-Jensen, M.P. Kuchera, R.R. Strauss

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2021

DOI: https://doi.org/10.1016/j.nima.2021.165461

URL: https://arxiv.org/abs/2008.02757

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

M. Almaeen, Y. Alanazi, N. Sato, W. Melnitchouk, M. P. Kuchera and Y. Li

2021 International Joint Conference on Neural Networks (IJCNN), 2021

DOI: 10.1109/IJCNN52387.2021.9534012

URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9534012&isnumber=9533267

Modeling Magnetohydrodynamic Equilibrium in Magnetars with Applications to Continuous Gravitational Wave Production

S. G. Frederick, M.P. Kuchera, Kristen L. Thompson

Monthly Notices of the Royal Astronomical Society, 2021

DOI: https://doi.org/10.1093/mnras/stab625

URL: https://academic.oup.com/mnras/article-abstract/503/2/2764/6164856

Bayesian Neural Networks for Fast SUSY Predictions

B. Kronheim, M.P. Kuchera, H.B. Prosper, A. Karbo

Physics Letters B, Volume 813, 2021

DOI: https://doi.org/10.1016/j.physletb.2020.136041

URL: https://www.sciencedirect.com/science/article/pii/S0370269320308224

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

L. Velasco, E. McClellan, N. Sato, P. Ambrozewicz, T. Liu, W. Melnitchouk, M.P. Kuchera, Yasir Alanazi, Yaohang Li

19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020

DOI: 10.1109/ICMLA51294.2020.00066

URL: https://ieeexplore.ieee.org/document/9356177

A.I. For Nuclear Physics

P. Bedaque, A. Boehnlein, M. Cromaz, M. Diefenthaler, L. Elouadrhiri, T. Horn, M.P. Kuchera, D. Lawrence, D. Lee, S. Lidia, R. McKeown, W. Melnitchouk, W. Nazarewicz, K. Orginos, Y. Roblin, M.S. Smith, M. Schram, Xin-Nian Wang

The European Physical Journal A, 57, 100, 2021

URL: https://link.springer.com/article/10.1140/epja/s10050-020-00290-x

Report from the A.I. For Nuclear Physics Workshop

P. Bedaque, A. Boehnlein, M. Cromaz, M. Diefenthaler, L. Elouadrhiri, T. Horn, M.P. Kuchera, D. Lawrence, D. Lee, S. Lidia, R. McKeown, W. Melnitchouk, W. Nazarewicz, K. Orginos, Y. Roblin, M.S. Smith, M. Schram, Xin-Nian Wang

Whitepaper for the Department of Energy and the National Science Foundation, 2020

URL: https://arxiv.org/pdf/2006.05422.pdf

Machine Learning Methods for Track Classification in the AT-TPC

M.P. Kuchera, R. Ramanujan, J.Z. Taylor, R.R. Strauss, D. Bazin, J. Bradt, R. Chen

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2019

DOI: https://doi.org/10.1016/j.nima.2019.05.097

URL: https://arxiv.org/pdf/1810.10350.pdf

Study of spectroscopic factors at N= 29 using isobaric analogue resonances in inverse kinematics

J. Bradt, Y. Ayyad, D. Bazin, W. Mittig, T. Ahn, S. Beceiro Novo, B.A. Brown, L. Carpenter, M. Cortesi, M.P. Kuchera, W.G. Lynch, S. Rost, N. Watwood, J. Yurkon, J. Barney, U. Datta, J. Estee, A. Gillibert, J. Manfredi, P. Morfouace, D. Pérez-Loureiro, E. Pollacco, J. Sammut, S. Sweany

Physics Letters B, 2018

DOI: https://doi.org/10.1016/j.physletb.2018.01.015

URL: https://www.sciencedirect.com/science/article/pii/S0370269318300236

Commissioning of the Active-Target Time Projection Chamber

J. Bradt, D. Bazin, F. Abu-Nimeh, T. Ahn, Y. Ayyad, S. Beceiro-Novo, L. Carpenter, M. Cortesi, M.P. Kuchera, W.G. Lynch, W. Mittig, S. Rost, N. Watwood, J. Yurkon

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2017

DOI: https://doi.org/10.1016/j.nima.2017.09.013

URL: https://www.sciencedirect.com/science/article/pii/S0168900217309683