Deep Learning Hamiltonian Monte Carlo. - Sam Foreman; Xiao-Yong Jin; James C. Osborn (CoRR, 2021)

LeapfrogLayers: A Trainable Framework for Effective Topological Sampling. - Sam Foreman; Xiao-Yong Jin; James C. Osborn (CoRR, 2021)

HMC with Normalizing Flows. - Sam Foreman; Taku Izubuchi; Luchang Jin; Xiao-Yong Jin; James C. Osborn; Akio Tomiya (CoRR, 2021)

Applications of Machine Learning to Lattice Quantum Field Theory. - Denis Boyda; Salvatore Calì; Sam Foreman; Lena Funcke; Daniel C. Hackett; Yin Lin; Gert Aarts; Andrei Alexandru; Xiao-Yong Jin; Biagio Lucini; Phiala E. Shanahan (CoRR, 2022)

A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators. - Murali Emani; Sam Foreman; Varuni Sastry; Zhen Xie; Siddhisanket Raskar; William Arnold; Rajeev Thakur; Venkatram Vishwanath; Michael E. Papka (CoRR, 2023)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. - Maxim Zvyagin; Alexander Brace; Kyle Hippe; Yuntian Deng; Bin Zhang; Cindy Orozco Bohorquez; Austin Clyde; Bharat Kale; Danilo Perez-Rivera; Heng Ma; Carla M. Mann; Michael W. Irvin; et al. (Int. J. High Perform. Comput. Appl., 2023)

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators. - Murali Emani; Sam Foreman; Varuni Sastry; Zhen Xie; Siddhisanket Raskar; William Arnold; Rajeev Thakur; Venkatram Vishwanath; Michael E. Papka; Sanjif Shanmugavelu; Darshan Gandhi; Hengyu Zhao; et al. (IPDPS (Workshops), 2024)

MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. - Gautham Dharuman; Kyle Hippe; Alexander Brace; Sam Foreman; Väinö Hatanpää; Varuni Katti Sastry; Huihuo Zheng; Logan T. Ward; Servesh Muralidharan; Archit Vasan; Bharat Kale; Carla M. Mann; et al. (SC, 2024)

Thorough Characterization and Analysis of Large Transformer Model Training At-Scale. - Scott Cheng; Jun-Liang Lin; Murali Emani; Siddhisanket Raskar; Sam Foreman; Zhen Xie; Venkatram Vishwanath; Mahmut Taylan Kandemir (Proc. ACM Meas. Anal. Comput. Syst., 2024)

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. - Ozan Gökdemir; Carlo Siebenschuh; Alexander Brace; Azton Wells; Brian Hsu; Kyle Hippe; Priyanka Setty; Aswathy Ajith; J. Gregory Pauloski; Varuni Sastry; Sam Foreman; Huihuo Zheng; et al. (PASC, 2025)

MOFA: Discovering Materials for Carbon Capture with a GenAI- and Simulation-Based Workflow. - Xiaoli Yan; Nathaniel Hudson; Hyun Park; Daniel Grzenda; J. Gregory Pauloski; Marcus Schwarting; Haochen Pan; Hassan Harb; Sam Foreman; Chris Knight 001; Tom Gibbs; Kyle Chard; et al. (CoRR, 2025)

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. - Ozan Gökdemir; Carlo Siebenschuh; Alexander Brace; Azton Wells; Brian Hsu; Kyle Hippe; Priyanka Vasanthakumari; Aswathy Ajith; J. Gregory Pauloski; Varuni Katti Sastry; Sam Foreman; Huihuo Zheng; et al. (CoRR, 2025)