Liquid water: obtaining the right answer for the right reasons. - Edoardo Aprà; Alistair P. Rendell; Robert J. Harrison; Vinod Tipparaju; Wibe A. de Jong; Sotiris S. Xantheas (SC, 2009)

Structures and Encapsulation Motifs of Functional Molecules Probed by Laser Spectroscopic and Theoretical Methods. - Ryoji Kusaka; Yoshiya Inokuchi; Sotiris S. Xantheas; Takayuki Ebata (Sensors, 2010)

HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data. - Sutanay Choudhury; Jenna A. Bilbrey; Logan T. Ward; Sotiris S. Xantheas; Ian T. Foster; Joseph P. Heindel; Ben Blaiszik; Marcus E. Schwarting (CoRR, 2020)

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)

Massively parallel quantum chemical density matrix renormalization group method. - Jiri Brabec; Jan Brandejs; Karol Kowalski; Sotiris S. Xantheas; Örs Legeza; Libor Veis (J. Comput. Chem., 2021)

Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators. - Jenna A. Bilbrey; Kristina M. Herman; Henry Sprueill; Sotiris S. Xantheas; Payel Das; Manuel Lopez Roldan; Mike Kraus; Hatem Helal; Sutanay Choudhury (CoRR, 2022)

Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry. - Hatem Helal; Jesun Firoz; Jenna A. Bilbrey; Mario Michael Krell; Tom Murray; Ang Li 006; Sotiris S. Xantheas; Sutanay Choudhury (CoRR, 2022)

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units. - Hatem Helal; Jesun Firoz; Jenna A. Bilbrey; Henry Sprueill; Kristina M. Herman; Mario Michael Krell; Tom Murray; Manuel Lopez Roldan; Mike Kraus; Ang Li 006; Payel Das; Sotiris S. Xantheas; et al. (J. Chem. Inf. Model., 2024)

Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE. - Jesun Firoz; Franco Pellegrini; Mario Geiger; Darren Hsu; Jenna A. Bilbrey; Han-Yi Chou; Maximilian Stadler; Markus Hoehnerbach; Tingyu Wang; Dejun Lin; Emine Küçükbenli; Henry W. Sprueill; et al. (CoRR, 2025)