Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems. - Alexander Wikner; Jaideep Pathak; Brian R. Hunt; Michelle Girvan; Troy Arcomano; Istvan Szunyogh; Andrew Pomerance; Edward Ott (CoRR, 2020)

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)

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. - Tung Nguyen; Rohan Shah; Hritik Bansal; Troy Arcomano; Sandeep Madireddy; Romit Maulik; Veerabhadra Kotamarthi; Ian T. Foster; Aditya Grover (CoRR, 2023)

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. - Tung Nguyen; Rohan Shah; Hritik Bansal; Troy Arcomano; Romit Maulik; Rao Kotamarthi; Ian T. Foster; Sandeep Madireddy; Aditya Grover (NeurIPS, 2024)

LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles. - Haiwen Guan; Troy Arcomano; Ashesh Chattopadhyay; Romit Maulik (CoRR, 2024)

Exploring the Potential of Hybrid Machine-Learning/Physics-Based Modeling for Atmospheric/Oceanic Prediction Beyond the Medium Range. - Dhruvit Patel; Troy Arcomano; Brian R. Hunt; Istvan Szunyogh; Edward Ott (CoRR, 2024)

CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints. - Xin Wang; Juntao Yang; Jeff Adie; Simon See; Kalli Furtado; Chen Chen; Troy Arcomano; Romit Maulik; Gianmarco Mengaldo (CoRR, 2025)

Multimodal Atmospheric Super-Resolution With Deep Generative Models. - Dibyajyoti Chakraborty; Haiwen Guan; Jason Stock; Troy Arcomano; Guido Cervone; Romit Maulik (CoRR, 2025)