Atmospheric Blocking Pattern Recognition in Global Climate Model Simulation Data. - Grzegorz Muszynski; Prabhat; Jan Balewski; Karthik Kashinath; Michael F. Wehner; Vitaliy Kurlin (ICPR, 2020)

Asynchronous I/O Strategy for Large-Scale Deep Learning Applications. - Sunwoo Lee 001; Qiao Kang; Kewei Wang 002; Jan Balewski; Alex Sim; Ankit Agrawal 001; Alok N. Choudhary; Peter Nugent; Kesheng Wu; Wei-keng Liao (HiPC, 2021)

MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. - Steven Farrell; Murali Emani; Jacob Balma; Lukas Drescher; Aleksandr Drozd; Andreas Fink; Geoffrey C. Fox; David Kanter; Thorsten Kurth; Peter Mattson; Dawei Mu; Amit Ruhela; et al. (MLHPC@SC, 2021)

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. - Steven Farrell; Murali Emani; Jacob Balma; Lukas Drescher; Aleksandr Drozd; Andreas Fink; Geoffrey C. Fox; David Kanter; Thorsten Kurth; Peter Mattson; Dawei Mu; Amit Ruhela; et al. (CoRR, 2021)

Co-design Center for Exascale Machine Learning Technologies (ExaLearn). - Francis J. Alexander; James A. Ang; Jenna A. Bilbrey; Jan Balewski; Tiernan Casey; Ryan Chard; Jong Choi 001; Sutanay Choudhury; Bert J. Debusschere; Anthony M. DeGennaro; Nikoli Dryden; J. Austin Ellis; et al. (Int. J. High Perform. Comput. Appl., 2021)

The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs With Hybrid Parallelism. - Yosuke Oyama; Naoya Maruyama; Nikoli Dryden; Erin McCarthy; Peter Harrington; Jan Balewski; Satoshi Matsuoka; Peter Nugent; Brian Van Essen (IEEE Trans. Parallel Distributed Syst., 2021)

Using Multi-Resolution Data to Accelerate Neural Network Training in Scientific Applications. - Kewei Wang 002; Sunwoo Lee 001; Jan Balewski; Alex Sim; Peter Nugent; Ankit Agrawal 001; Alok N. Choudhary; Kesheng Wu; Wei-Keng Liao (CCGRID, 2022)

Time-series ML-regression on Graphcore IPU-M2000 and Nvidia A100. - Jan Balewski; Zhenying Liu; Alexander Tsyplikhin; Manuel Lopez Roland; Kristofer E. Bouchard (PMBS@SC, 2022)

Scaling and Benchmarking an Evolutionary Algorithm for Constructing Biophysical Neuronal Models. - Alexander Ladd; Kyung Geun Kim; Jan Balewski; Kristofer E. Bouchard; Roy Ben-Shalom (Frontiers Neuroinformatics, 2022)

Efficient Quantum Counting and Quantum Content-Addressable Memory for DNA Similarity. - Jan Balewski; Daan Camps; Katherine Klymko; Andrew J. Tritt (QCE, 2023)

Quantum Computing and Visualization: A Disruptive Technological Change Ahead. - E. Wes Bethel; Mercy G. Amankwah; Jan Balewski; Roel Van Beeumen; Daan Camps; Daniel Huang 001; Talita Perciano (IEEE Computer Graphics and Applications, 2023)

Engineering Quantum States with Neutral Atoms. - Jan Balewski; Milan Kornjaca; Katherine Klymko; Siva Darbha; Mark R. Hirsbrunner; Pedro L. S. Lopes; Fangli Liu; Daan Camps (QCE, 2024)

QubiCML: ML-Powered Real-Time Quantum State Discrimination Enabling Mid-Circuit Measurements. - Neel R. Vora; Yilun Xu; Akel Hasim; Neelay Fruitwala; Nam Nguyen; Horan Liao; Jan Balewski; Abhi D. Rajagopala; Kasra Nowrouzi; Qing Ji; K. Birgitta Whaley; Irfan Siddiqi; et al. (QCE, 2024)