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)

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)

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)

Ultra Fast Transformers on FPGAs for Particle Physics Experiments. - Zhixing Jiang; Dennis Yin; Elham E Khoda; Vladimir Loncar; Ekaterina Govorkova; Eric A. Moreno; Philip C. Harris; Scott Hauck; Shih-Chieh Hsu (CoRR, 2024)

FPGA Deployment of LFADS for Real-time Neuroscience Experiments. - Xiaohan Liu; Chi-Jui Chen; YanLun Huang; LingChi Yang; Elham E Khoda; Yihui Chen; Scott Hauck; Shih-Chieh Hsu; Bo-Cheng Lai (CoRR, 2024)

Low Latency Transformer Inference on FPGAs for Physics Applications with hls4ml. - Zhixing Jiang; Dennis Yin; Yihui Chen; Elham E Khoda; Scott Hauck; Shih-Chieh Hsu; Ekaterina Govorkova; Philip C. Harris; Vladimir Loncar; Eric A. Moreno (CoRR, 2024)

FAIR Universe HiggsML Uncertainty Challenge Competition. - Wahid Bhimji; Paolo Calafiura; Ragansu Chakkappai; Yuan-Tang Chou; Sascha Diefenbacher; Jordan Dudley; Steven Farrell; Aishik Ghosh; Isabelle Guyon; Chris Harris; Shih-Chieh Hsu; Elham E Khoda; et al. (CoRR, 2024)

Interpreting Transformers for Jet Tagging. - Aaron Wang; Abhijith Gandrakota; Jennifer Ngadiuba; Vivekanand Sahu; Priyansh Bhatnagar; Elham E Khoda; Javier M. Duarte (CoRR, 2024)

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)

The National Research Platform: Stretched, Multi-Tenant, Scientific Kubernetes Cluster. - Derek Weitzel; Ashton Graves; Sam Albin; Huijun Zhu; Frank Würthwein; Mahidhar Tatineni; Dmitry Mishin; John J. Graham; Elham E Khoda; Mohammad Firas Sada; Larry Smarr; Thomas A. DeFanti (CoRR, 2025)

Serving LLMs in HPC Clusters: A Comparative Study of Qualcomm Cloud AI 100 Ultra and High-Performance GPUs. - Mohammad Firas Sada; John J. Graham; Elham E Khoda; Mahidhar Tatineni; Dmitry Mishin; Rajesh K. Gupta; Rick Wagner; Larry Smarr; Thomas A. DeFanti; Frank Würthwein (CoRR, 2025)