Accelerating Recurrent Neural Networks for Gravitational Wave Experiments. - Zhiqiang Que; Erwei Wang; Umar Marikar; Eric A. Moreno; Jennifer Ngadiuba; Hamza Javed; Bartlomiej Borzyszkowski; Thea Aarrestad; Vladimir Loncar; Sioni Summers; Maurizio Pierini; Peter Y. K. Cheung; et al. (ASAP, 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)

Source-agnostic gravitational-wave detection with recurrent autoencoders. - Eric A. Moreno; Bartlomiej Borzyszkowski; Maurizio Pierini; Jean-Roch Vlimant; Maria Spiropulu (Mach. Learn. Sci. Technol., 2022)

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)

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)

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)

Rapid likelihood free inference of compact binary coalescences using accelerated hardware. - Deep Chatterjee; Ethan Marx; William Benoit; Ravi Kumar; Malina Desai; Ekaterina Govorkova; Alec Gunny; Eric A. Moreno; Rafia Omer; Ryan Raikman; Muhammed Saleem; Shrey Aggarwal; et al. (Mach. Learn. Sci. Technol., 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)

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)