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)

A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC. - Giuseppe Di Guglielmo; Farah Fahim; Christian Herwig; Manuel Blanco Valentin; Javier M. Duarte; Cristian Gingu; Philip C. Harris; James Hirschauer; Martin Kwok; Vladimir Loncar; Yingyi Luo; Llovizna Miranda; 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)

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)

FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning. - Javier M. Duarte; Nhan Tran; Benjamin Hawks; Christian Herwig; Jules Muhizi; Shvetank Prakash; Vijay Janapa Reddi (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)

Differentiable Earth mover's distance for data compression at the high-luminosity LHC. - Rohan Shenoy; Javier M. Duarte; Christian Herwig; James Hirschauer; Daniel Noonan; Maurizio Pierini; Nhan Tran; Cristina Mantilla Suarez (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)