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)

Stacked Generative Machine Learning Models for Fast Approximations of Steady-State Navier-Stokes Equations. - Shen Wang 007; Mehdi Nikfar; Joshua C. Agar; Yaling Liu (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. (Frontiers Big Data, 2022)

Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy. - Sergei V. Kalinin; Debangshu Mukherjee; Kevin M. Roccapriore; Ben Blaiszik; Ayana Ghosh; Maxim A. Ziatdinov; Anees Al-Najjar; Christina Doty; Sarah Akers; Nageswara S. V. Rao; Joshua C. Agar; Steven R. Spurgeon (CoRR, 2023)

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak. - Yumou Wei; Ryan F. Forelli; Chris Hansen; Jeffrey P. Levesque; Nhan Tran; Joshua C. Agar; Giuseppe Di Guglielmo; Michael E. Mauel; Gerald A. Navratil (CoRR, 2023)

Data Discovery and Indexing for Semi-Structured Scientific Data. - Kaushik Jagini; Yifan Zhang; Yichen Guo; Julian Goddy; Dale Stansberry; Joshua Agar; Jeff Heflin (ICEIS (2), 2024)

Making Sense of Metadata Mess: Alignment and Risk Assessment for Diatom Data Use Case. - Kio Polson; Marina Potapova; Uttam Meena; Chad Peiper; Joshua Brown 006; Joshua Agar; Jane Greenberg (MTSR, 2024)

A Wireless Monitoring System to Quantify Indoor-Outdoor Air Pollution in a Building. - John Edrick M. Gador; Lance H. Atienza; John Danielle T. Castor; Nathan Andrei A. Galang; Marc D. Rosales; Percival Magpantay; Julius Rhoan Lustro; Joshua C. Agar; John Jairus D. P. Eslit; Carlo Elpidio Capiral; John Richard E. Hizon (TENCON, 2024)

Reliable edge machine learning hardware for scientific applications. - Tommaso Baldi; Javier Campos; Benjamin Hawks; Jennifer Ngadiuba; Nhan Tran; Daniel Diaz 003; Javier M. Duarte; Ryan Kastner; Andres Meza 001; Melissa Quinnan; Olivia Weng; Caleb Geniesse; et al. (VTS, 2024)

A High Level Synthesis Methodology for Dynamic Monitoring of FPGA ML Accelerators. - Ryan F. Forelli; Rui Shi; Seda Ogrenci; Joshua Agar (VTS, 2024)

Making Sense of Metadata Mess: Alignment & Risk Assessment for Diatom Data Use Case. - Kio Polson; Marina Potapova; Uttam Meena; Chad Peiper; Joshua Brown 006; Joshua Agar; Jane Greenberg (CoRR, 2024)

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)

Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning. - Khayrul Islam; Ryan F. Forelli; Jianzhong Han; Deven Bhadane; Jian Huang; Joshua C. Agar; Nhan Tran; Seda Ogrenci; Yaling Liu (CoRR, 2025)