Strategies for Modeling Extreme Luminosities in the CMS Simulation. - Michael D. Hildreth; Elizabeth Sexton-Kennedy; Kevin Pedro; Matti Kortelainen (eScience, 2018)

Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan". - James F. Amundson; James Annis; Camille Avestruz; D. Bowring; João Caldeira; Giuseppe Cerati; Chihway L. Chang; Scott Dodelson; D. Elvira; A. Farahi; Krzysztof L. Genser; Lindsey Gray; et al. (CoRR, 2019)

FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing. - Javier M. Duarte; Philip C. Harris; Scott Hauck; Burt Holzman; Shih-Chieh Hsu; Sergo Jindariani; Suffian Khan; Benjamin Kreis; Brian Lee; Mia Liu; Vladimir Loncar; Jennifer Ngadiuba; et al. (Comput. Softw. Big Sci., 2019)

FPGAs-as-a-Service Toolkit (FaaST). - Dylan S. Rankin; Jeffrey D. Krupa; Philip C. Harris; Maria Acosta Flechas; Burt Holzman; Thomas Klijnsma; Kevin Pedro; Nhan Tran; Scott Hauck; Shih-Chieh Hsu; Matthew Trahms; Kelvin Lin; et al. (H2RC@SC, 2020)

GPU coprocessors as a service for deep learning inference in high energy physics. - Jeffrey D. Krupa; Kelvin Lin; Maria Acosta Flechas; Jack Dinsmore; Javier M. Duarte; Philip C. Harris; Scott Hauck; Burt Holzman; Shih-Chieh Hsu; Thomas Klijnsma; Mia Liu; Kevin Pedro; et al. (CoRR, 2020)

Coffea - Columnar Object Framework For Effective Analysis. - Nicholas Smith; Lindsey Gray; Matteo Cremonesi; Bo Jayatilaka; Oliver Gutsche; Allison Hall; Kevin Pedro; Maria Acosta Flechas; Andrew Melo; Stefano Belforte; Jim Pivarski (CoRR, 2020)

Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. - Yutaro Iiyama; Gianluca Cerminara; Abhijay Gupta; Jan Kieseler; Vladimir Loncar; Maurizio Pierini; Shah Rukh Qasim; Marcel Rieger; Sioni Summers; Gerrit Van Onsem; Kinga Anna Wozniak; Jennifer Ngadiuba; et al. (Frontiers Big Data, 2020)

GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments. - Michael Wang 003; Tingjun Yang; Maria Acosta Flechas; Philip C. Harris; Benjamin Hawks; Burt Holzman; Kyle Knoepfel; Jeffrey D. Krupa; Kevin Pedro; Nhan Tran (Frontiers Big Data, 2020)

Fast convolutional neural networks on FPGAs with hls4ml. - Thea Aarrestad; Vladimir Loncar; Maurizio Pierini; Sioni Summers; Jennifer Ngadiuba; Christoffer Petersson; Hampus Linander; Yutaro Iiyama; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Dylan S. Rankin; et al. (CoRR, 2021)

Robustness of deep learning algorithms in astronomy - galaxy morphology studies. - Aleksandra Ciprijanovic; Diana Kafkes; Gabriel N. Perdue; Kevin Pedro; Gregory F. Snyder; F. Javier Sánchez; Sandeep Madireddy; Stefan M. Wild; Brian Nord (CoRR, 2021)

Autoencoders for Semivisible Jet Detection. - Florencia Canelli; Annapaola de Cosa; Luc Le Pottier; Jeremi Niedziela; Kevin Pedro; Maurizio Pierini (CoRR, 2021)

GeantV. - Guilherme Amadio; A. Ananya; John Apostolakis; Marilena Bandieramonte; S. Banerjee; Abhijit Bhattacharyya; Calebe P. Bianchini; G. Bitzes; Philippe Canal; Federico Carminati; Oscar Roberto Chaparro-Amaro; Gabriele Cosmo; et al. (Comput. Softw. Big Sci., 2021)

Fast convolutional neural networks on FPGAs with hls4ml. - Thea Aarrestad; Vladimir Loncar; Nicolò Ghielmetti; Maurizio Pierini; Sioni Summers; Jennifer Ngadiuba; Christoffer Petersson; Hampus Linander; Yutaro Iiyama; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; et al. (Mach. Learn. Sci. Technol., 2021)

GPU coprocessors as a service for deep learning inference in high energy physics. - Jeffrey D. Krupa; Kelvin Lin; Maria Acosta Flechas; Jack Dinsmore; Javier M. Duarte; Philip C. Harris; Scott Hauck; Burt Holzman; Shih-Chieh Hsu; Thomas Klijnsma; Mia Liu; Kevin Pedro; et al. (Mach. Learn. Sci. Technol., 2021)

Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml. - Jennifer Ngadiuba; Vladimir Loncar; Maurizio Pierini; Sioni Summers; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Dylan S. Rankin; Sergo Jindariani; Mia Liu; Kevin Pedro; Nhan Tran; et al. (Mach. Learn. Sci. Technol., 2021)

New directions for surrogate models and differentiable programming for High Energy Physics detector simulation. - Andreas Adelmann; Walter Hopkins; Evangelos Kourlitis; Michael Kagan; Gregor Kasieczka; Claudius Krause; David Shih; Vinicius Mikuni; Benjamin Nachman; Kevin Pedro; Daniel Winklehner (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)

Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. - Aleksandra Ciprijanovic; Ashia Lewis; Kevin Pedro; Sandeep Madireddy; Brian Nord; Gabriel N. Perdue; Stefan M. Wild (CoRR, 2022)

DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification. - Aleksandra Ciprijanovic; Diana Kafkes; Gregory F. Snyder; F. Javier Sánchez; Gabriel Nathan Perdue; Kevin Pedro; Brian Nord; Sandeep Madireddy; Stefan M. Wild (Mach. Learn. Sci. Technol., 2022)

DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection. - Aleksandra Ciprijanovic; Ashia Lewis; Kevin Pedro; Sandeep Madireddy; Brian Nord; Gabriel N. Perdue; Stefan M. Wild (Mach. Learn. Sci. Technol., 2023)

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing. - Tejin Cai; Kenneth Herner; Tingjun Yang; Michael Wang 003; Maria Acosta Flechas; Philip C. Harris; Burt Holzman; Kevin Pedro; Nhan Tran (Comput. Softw. Big Sci., 2023)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. - Claudius Krause; Michele Faucci Giannelli; Gregor Kasieczka; Benjamin Nachman; Dalila Salamani; David Shih; Anna Zaborowska; Oz Amram; Kerstin Borras; Matthew R. Buckley; Erik Buhmann; Thorsten Buss; et al. (CoRR, 2024)

Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server. - Claire Savard; Nicholas Manganelli; Burt Holzman; Lindsey Gray; Alexx Perloff; Kevin Pedro; Kevin Stenson; Keith Ulmer (Comput. Softw. Big Sci., 2024)

Track reconstruction as a service for collider physics. - Haoran Zhao; Yuan-Tang Chou; Yao Yao; Xiangyang Ju; Yongbin Feng; William Patrick McCormack; Miles Cochran-Branson; Jan-Frederik Schulte; Miaoyuan Liu; Javier M. Duarte; Philip Harris; Shih-Chieh Hsu; 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)