Output-Constrained Bayesian Neural Networks. - Wanqian Yang; Lars Lorch; Moritz A. Graule; Srivatsan Srinivasan; Anirudh Suresh; Jiayu Yao; Melanie F. Pradier; Finale Doshi-Velez (CoRR, 2019)

Multi-objective Coevolution and Decision-making for Cooperative and Competitive Environments. - Anirudh Suresh; Jaturong Kongmanee; Kalyanmoy Deb; Vishnu Naresh Boddeti (CEC, 2021)

Towards Multi-objective Co-evolutionary Problem Solving. - Anirudh Suresh; Kalyanmoy Deb; Vishnu Naresh Boddeti (EMO, 2021)

A Survey on Evaluation Metrics for Synthetic Material Micro-Structure Images from Generative Models. - Devesh Shah; Anirudh Suresh; Alemayehu Admasu; Devesh Upadhyay; Kalyanmoy Deb (CoRR, 2022)

Learning to Predict Pareto-Optimal Solutions from Pseudo-weights. - Kalyanmoy Deb; Aryan Gondkar; Anirudh Suresh (EMO, 2023)

On the Choice of Unique Identifiers for Predicting Pareto-Optimal Solutions Using Machine Learning. - Anirudh Suresh; Kalyanmoy Deb (SSCI, 2023)

On a Better Understanding of Unique Identifiers of Pareto Solutions for Multi-criterion Optimization, Visualization, and Decision-making. - Anirudh Suresh; Kalyanmoy Deb (CEC, 2024)

Machine Learning-Based Prediction of New Pareto-Optimal Solutions From Pseudo-Weights. - Anirudh Suresh; Kalyanmoy Deb (IEEE Trans. Evol. Comput., 2024)

Distinguishing Quantum Software Bugs from Hardware Noise: A Statistical Approach. - Ahmik Virani; Devraj; Anirudh Suresh; Lei Zhang; M. V. Panduranga Rao (CoRR, 2025)