Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications. - Javier M. Duarte; Song Han 003; Philip C. Harris; Sergo Jindariani; Edward Kreinar; Benjamin Kreis; Vladimir Loncar; Jennifer Ngadiuba; Maurizio Pierini; Dylan S. Rankin; Ryan A. Rivera; Sioni Summers; et al. (FPGA, 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)

AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters. - Naif Tarafdar; Giuseppe Di Guglielmo; Philip C. Harris; Jeffrey D. Krupa; Vladimir Loncar; Dylan S. Rankin; Nhan Tran; Zhenbin Wu; Qianfeng Shen; Paul Chow (FCCM, 2020)

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)

Fast inference of Boosted Decision Trees in FPGAs for particle physics. - Sioni Summers; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Duc Hoang; Sergo Jindariani; Edward Kreinar; Vladimir Loncar; Jennifer Ngadiuba; Maurizio Pierini; Dylan S. Rankin; Nhan Tran; 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)

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)

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)

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices. - Farah Fahim; Benjamin Hawks; Christian Herwig; James Hirschauer; Sergo Jindariani; Nhan Tran; Luca P. Carloni; Giuseppe Di Guglielmo; Philip C. Harris; Jeffrey D. Krupa; Dylan S. Rankin; Manuel Blanco Valentin; 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)

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)

A Software Ecosystem for Deploying Deep Learning in Gravitational Wave Physics. - Alec Gunny; Dylan S. Rankin; Philip C. Harris; Erik Katsavounidis; Ethan Marx; Muhammed Saleem; Michael Coughlin; William Benoit (FlexScience@HPDC, 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)

AIgean: An Open Framework for Deploying Machine Learning on Heterogeneous Clusters. - Naif Tarafdar; Giuseppe Di Guglielmo; Philip C. Harris; Jeffrey D. Krupa; Vladimir Loncar; Dylan S. Rankin; Nhan Tran; Zhenbin Wu; Qianfeng Shen; Paul Chow (ACM Trans. Reconfigurable Technol. Syst., 2022)

Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml. - Elham E Khoda; Dylan S. Rankin; Rafael Teixeira de Lima; Philip C. Harris; Scott Hauck; Shih-Chieh Hsu; Michael Kagan; Vladimir Loncar; Chaitanya Paikara; Richa Rao; Sioni Summers; Caterina Vernieri; et al. (Mach. Learn. Sci. Technol., 2023)

MACK: Mismodeling Addressed with Contrastive Knowledge. - Liam Rankin Sheldon; Dylan Sheldon Rankin; Philip C. Harris (CoRR, 2024)

A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run. - Ryan Raikman; Eric A. Moreno; Katya Govorkova; Siddharth Soni; Ethan Marx; William Benoit; Alec Gunny; Deep Chatterjee; Christina Reissel; Malina Desai; Rafia Omer; Muhammed Saleem; et al. (CoRR, 2024)

GWAK: gravitational-wave anomalous knowledge with recurrent autoencoders. - Ryan Raikman; Eric A. Moreno; Ekaterina Govorkova; Ethan Marx; Alec Gunny; William Benoit; Deep Chatterjee; Rafia Omer; Muhammed Saleem; Dylan S. Rankin; Michael W. Coughlin; Philip C. Harris; et al. (Mach. Learn. Sci. Technol., 2024)

SymbolFit: Automatic Parametric Modeling with Symbolic Regression. - Ho Fung Tsoi; Dylan S. Rankin; Cecile Caillol; Miles D. Cranmer; Sridhara Dasu; Javier M. Duarte; Philip C. Harris; Elliot Lipeles; Vladimir Loncar (Comput. Softw. Big Sci., 2025)