Deep learning long-range information in undirected graphs with wave networks. - Matthew K. Matlock; Arghya Datta; Na Le Dang; Kevin Jiang; S. Joshua Swamidass (IJCNN, 2019)

Cal-Net: Jointly Learning Classification and Calibration On Imbalanced Binary Classification Tasks. - Arghya Datta; Noah R. Flynn; S. Joshua Swamidass (IJCNN, 2021)

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort. - Arghya Datta; Noah R. Flynn; Dustyn A. Barnette; Keith F. Woeltje; Grover P. Miller; S. Joshua Swamidass (PLoS Comput. Biol., 2021)

'Black Box' to 'Conversational' Machine Learning: Ondansetron Reduces Risk of Hospital-Acquired Venous Thromboembolism. - Arghya Datta; Matthew K. Matlock; Na Le Dang; Thiago C. Moulin; Keith F. Woeltje; Elizabeth L. Yanik; Sanjay Joshua Swamidass (IEEE J. Biomed. Health Informatics, 2021)

Fair-Net: A Network Architecture for Reducing Performance Disparity between Identifiable Sub-populations. - Arghya Datta; S. Joshua Swamidass (ICAART (3), 2022)

Measuring and Mitigating Local Instability in Deep Neural Networks. - Arghya Datta; Subhrangshu Nandi; Jingcheng Xu; Greg Ver Steeg; He Xie; Anoop Kumar; Aram Galstyan (ACL (Findings), 2023)

On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis. - Arghya Datta; Sayak Chakrabarty (NeurIPS, 2023)

Exponential Convergence of CAVI for Bayesian PCA. - Arghya Datta; Philippe Gagnon; Florian Maire (CoRR, 2025)

SOP-Bench: Complex Industrial SOPs for Evaluating LLM Agents. - Subhrangshu Nandi; Arghya Datta; Nikhil Vichare; Indranil Bhattacharya; Huzefa Raja; Jing Xu; Shayan Ray; Giuseppe Carenini; Abhi Srivastava; Aaron Chan; Man Ho Woo; Amar Kandola; et al. (CoRR, 2025)