Machine learning at the energy and intensity frontiers of particle physics. - Alexander Radovic; Mike Williams; David Rousseau; Michael Kagan; Daniele Bonacorsi; Alexander Himmel; Adam Aurisano; Kazuhiro Terao; Taritree Wongjirad (Nat., 2018)

Scalable Deep Convolutional Neural Networks for Sparse, Locally Dense Liquid Argon Time Projection Chamber Data. - Laura Dominé; Kazuhiro Terao (CoRR, 2019)

PILArNet: Public Dataset for Particle Imaging Liquid Argon Detectors in High Energy Physics. - Corey Adams; Kazuhiro Terao; Taritree Wongjirad (CoRR, 2020)

Point Proposal Network for Reconstructing 3D Particle Positions with Sub-Pixel Precision in Liquid Argon Time Projection Chambers. - Laura Dominé; Kazuhiro Terao (CoRR, 2020)

Track Seeding and Labelling with Embedded-space Graph Neural Networks. - Nicholas Choma; Daniel Murnane; Xiangyang Ju; Paolo Calafiura; Sean Conlon; Steven Farrell; Prabhat; Giuseppe Cerati; Lindsey Gray; Thomas Klijnsma; Jim Kowalkowski; Panagiotis Spentzouris; et al. (CoRR, 2020)

Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data. - François Drielsma; Qing Lin; Pierre Côte de Soux; Laura Dominé; Ran Itay; Dae Heun Koh; Bradley J. Nelson; Kazuhiro Terao; Ka Vang Tsang; Tracy L. Usher (CoRR, 2020)

Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers. - Dae Heun Koh; Pierre Côte de Soux; Laura Dominé; François Drielsma; Ran Itay; Qing Lin; Kazuhiro Terao; Ka Vang Tsang; Tracy L. Usher (CoRR, 2020)

Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors. - François Drielsma; Kazuhiro Terao; Laura Dominé; Dae Heun Koh (CoRR, 2021)

Artificial Intelligence for High Energy Physics - Paolo Calafiura; David Rousseau; Kazuhiro Terao (WorldScientific, 2022)

Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges. - Savannah Thais; Paolo Calafiura; Grigorios Chachamis; Gage DeZoort; Javier M. Duarte; Sanmay Ganguly; Michael Kagan; Daniel Murnane; Mark S. Neubauer; Kazuhiro Terao (CoRR, 2022)

Data Science and Machine Learning in Education. - Gabriele Benelli; Thomas Y. Chen; Javier M. Duarte; Matthew Feickert; Matthew J. Graham; Lindsey Gray; Dan Hackett; Philip C. Harris; Shih-Chieh Hsu; Gregor Kasieczka; Elham E Khoda; Matthias Komm; et al. (CoRR, 2022)

Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning. - Phiala E. Shanahan; Kazuhiro Terao; Daniel Whiteson (CoRR, 2022)

Implicit Neural Representation as a Differentiable Surrogate for Photon Propagation in a Monolithic Neutrino Detector. - Minjie Lei; Ka Vang Tsang; Sean Gasiorowski; Chuan Li; Youssef S. G. Nashed; Gianluca Petrillo; Olivia Piazza; Daniel Ratner; Kazuhiro Terao (CoRR, 2022)

Differentiable simulation of a liquid argon time projection chamber. - Sean Gasiorowski; Yifan Chen; Youssef S. G. Nashed; Pierre Granger; Camelia Mironov; Ka Vang Tsang; Daniel Ratner; Kazuhiro Terao (Mach. Learn. Sci. Technol., 2024)

Particle Trajectory Representation Learning with Masked Point Modeling. - Sam Young; Yeon-jae Jwa; Kazuhiro Terao (CoRR, 2025)