Container solutions for HPC Systems: A Case Study of Using Shifter on Blue Waters. - Maxim Belkin; Roland Haas; Galen Wesley Arnold; Hon Wai Leong; Eliu A. Huerta; David Lesny; Mark S. Neubauer (PEARC, 2018)

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era. - Gabrielle Allen; Igor Andreoni; Etienne Bachelet; G. Bruce Berriman; Federica B. Bianco; Rahul Biswas; Matias Carrasco Kind; Kyle Chard; Minsik Cho; Philip S. Cowperthwaite; Zachariah B. Etienne; Daniel George; et al. (CoRR, 2019)

Enabling real-time multi-messenger astrophysics discoveries with deep learning. - Eliu A. Huerta; Gabrielle Allen; Igor Andreoni; Javier Mauricio Antelis; Etienne Bachelet; G. Bruce Berriman; Federica B. Bianco; Rahul Biswas; Matias Carrasco Kind; Kyle Chard; Minsik Cho; Philip S. Cowperthwaite; et al. (CoRR, 2019)

Supporting High-Performance and High-Throughput Computing for Experimental Science. - Eliu A. Huerta; Roland Haas; Shantenu Jha; Mark S. Neubauer; Daniel S. Katz (Comput. Softw. Big Sci., 2019)

The Scalable Systems Laboratory: a Platform for Software Innovation for HEP. - Robert W. Gardner; Lincoln Bryant; Mark S. Neubauer; Frank Würthwein; Judith Stephen; Andrew A. Chien (CoRR, 2020)

Software Sustainability & High Energy Physics. - Daniel S. Katz; Sudhir Malik; Mark S. Neubauer; Graeme Andrew Stewart; Kétévi A. Assamagan; Erin A. Becker; Neil P. Chue Hong; Ian A. Cosden; Samuel Meehan; Edward J. W. Moyse; Adrian M. Price-Whelan; Elizabeth Sexton-Kennedy; et al. (CoRR, 2020)

Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs. - Aneesh Heintz; Vesal Razavimaleki; Javier M. Duarte; Gage DeZoort; Isobel Ojalvo; Savannah Thais; Markus Atkinson; Mark S. Neubauer; Lindsey Gray; Sergo Jindariani; Nhan Tran; Philip C. Harris; et al. (CoRR, 2020)

Physics and Computing Performance of the Exa.TrkX TrackML Pipeline. - Xiangyang Ju; Daniel Murnane; Paolo Calafiura; Nicholas Choma; Sean Conlon; Steven Farrell; Yaoyuan Xu; Maria Spiropulu; Jean-Roch Vlimant; Adam Aurisano; Jeremy Hewes; Giuseppe Cerati; et al. (CoRR, 2021)

A FAIR and AI-ready Higgs Boson Decay Dataset. - Yifan Chen; Eliu A. Huerta; Javier M. Duarte; Philip C. Harris; Daniel S. Katz; Mark S. Neubauer; Daniel Diaz 003; Farouk Mokhtar; Raghav Kansal; Sang Eon Park; Volodymyr V. Kindratenko; Zhizhen Zhao 001; et al. (CoRR, 2021)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (CoRR, 2021)

Graph Neural Networks for Charged Particle Tracking on FPGAs. - Abdelrahman Elabd; Vesal Razavimaleki; Shi-Yu Huang; Javier M. Duarte; Markus Atkinson; Gage DeZoort; Peter Elmer; Jin-Xuan Hu; Shih-Chieh Hsu; Bo-Cheng Lai; Mark S. Neubauer; Isobel Ojalvo; et al. (CoRR, 2021)

Charged Particle Tracking via Edge-Classifying Interaction Networks. - Gage DeZoort; Savannah Thais; Javier M. Duarte; Vesal Razavimaleki; Markus Atkinson; Isobel Ojalvo; Mark S. Neubauer; Peter Elmer (Comput. Softw. Big Sci., 2021)

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)

Physics Community Needs, Tools, and Resources for Machine Learning. - Philip C. Harris; Erik Katsavounidis; William Patrick McCormack; Dylan S. Rankin; Yongbin Feng; Abhijith Gandrakota; Christian Herwig; Burt Holzman; Kevin Pedro; Nhan Tran; Tingjun Yang; Jennifer Ngadiuba; et al. (CoRR, 2022)

Explainable AI for High Energy Physics. - Mark S. Neubauer; Avik Roy (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 CompF4 Topical Group Report: Storage and Processing Resource Access. - W. Bhimij; Dale Carder; Eli Dart; Javier M. Duarte; Ian Fisk; Robert W. Gardner; Chin Guok; Bo Jayatilaka; Tom Lehman; M. Lin; Carlos Maltzahn; Shawn McKee; et al. (CoRR, 2022)

FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. - Eliu A. Huerta; Ben Blaiszik; L. Catherine Brinson; Kristofer E. Bouchard; Daniel Diaz 003; Caterina Doglioni; Javier M. Duarte; Murali Emani; Ian T. Foster; Geoffrey C. Fox; Philip C. Harris; Lukas Heinrich; et al. (CoRR, 2022)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (Frontiers Big Data, 2022)

Graph Neural Networks for Charged Particle Tracking on FPGAs. - Abdelrahman Elabd; Vesal Razavimaleki; Shi-Yu Huang; Javier M. Duarte; Markus Atkinson; Gage DeZoort; Peter Elmer; Scott Hauck; Jin-Xuan Hu; Shih-Chieh Hsu; Bo-Cheng Lai; Mark S. Neubauer; et al. (Frontiers Big Data, 2022)

Low Latency Edge Classification GNN for Particle Trajectory Tracking on FPGAs. - Shi-Yu Huang; Yun-Chen Yang; Yu-Ru Su; Bo-Cheng Lai; Javier M. Duarte; Scott Hauck; Shih-Chieh Hsu; Jin-Xuan Hu; Mark S. Neubauer (FPL, 2023)

A detailed study of interpretability of deep neural network based top taggers. - Ayush Khot; Mark S. Neubauer; Avik Roy (Mach. Learn. Sci. Technol., 2023)

Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access. - Wahid Bhimji; Dale Carder; Eli Dart; Javier M. Duarte; Ian Fisk; Robert W. Gardner; Chin Guok; Bo Jayatilaka; Tom Lehman; M. Lin; Carlos Maltzahn; Shawn McKee; et al. (Comput. Softw. Big Sci., 2023)

FAIR AI models in high energy physics. - Javier M. Duarte; Haoyang Li 019; Avik Roy; Ruike Zhu; Eliu A. Huerta; Daniel Diaz 003; Philip C. Harris; Raghav Kansal; Daniel S. Katz; Ishaan H. Kavoori; Volodymyr V. Kindratenko; Farouk Mokhtar; et al. (Mach. Learn. Sci. Technol., 2023)

Corrigendum: Applications and techniques for fast machine learning in science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci-Memik; et al. (Frontiers Big Data, 2024)

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning. - Jieun Yoo; Jennet Dickinson; Morris Swartz; Giuseppe Di Guglielmo; Alice Bean; Douglas Berry; Manuel Blanco Valentin; Karri Dipetrillo; Farah Fahim; Lindsey Gray; James Hirschauer; Shruti R. Kulkarni; et al. (Mach. Learn. Sci. Technol., 2024)

HiGTR: High-Performance FPGA Implementation of Complete GNN-based Trajectory Reconstruction for HEP. - Yun-Chen Yang; Hsuan-Wei Yu; Bo-Cheng Lai; Shih-Chieh Hsu; Mark S. Neubauer; Santosh Parajuli (FPGA, 2025)

From Signals to Features to Insights: Multi-Level Novelty Detection for Fast Scientific Discovery. - Devashri Naik; Nastaran Darabi; Sina Tayebati; Dinithi Jayasuriya; Shamma Nasrin; Danush Shekar; Corrinne Mills; Benjamin Parpillon; Farah Fahim; Mark S. Neubauer; Amit Ranjan Trivedi (VTS, 2025)

Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural Networks. - Ayush Khot; Xiwei Wang; Avik Roy; Volodymyr V. Kindratenko; Mark S. Neubauer (CoRR, 2025)

Building Machine Learning Challenges for Anomaly Detection in Science. - Elizabeth G. Campolongo; Yuan-Tang Chou; Ekaterina Govorkova; Wahid Bhimji; Wei-Lun Chao; Chris Harris; Shih-Chieh Hsu; Hilmar Lapp; Mark S. Neubauer; Josephine M. Namayanja; Aneesh Subramanian; Philip C. Harris; et al. (CoRR, 2025)

Analysis Facilities for the HL-LHC White Paper. - Diego Ciangottini; Alessandra Forti; Lukas Heinrich; Nicola Skidmore; C. Alpigiani; M. Aly; D. Benjamin; B. Bockelman; L. Bryant; J. Catmore; M. D'Alfonso; Antonio Delgado Peris; et al. (Comput. Softw. Big Sci., 2025)