Modeling Network Growth under Resource Constraints. - Harshay Shah; Suhansanu Kumar; Hari Sundaram (CoRR, 2017)

Number of Connected Components in a Graph: Estimation via Counting Patterns. - Ashish Khetan; Harshay Shah; Sewoong Oh (CoRR, 2018)

Growing Attributed Networks through Local Processes. - Harshay Shah; Suhansanu Kumar; Hari Sundaram (WWW, 2019)

The Pitfalls of Simplicity Bias in Neural Networks. - Harshay Shah; Kaustav Tamuly; Aditi Raghunathan; Prateek Jain 002; Praneeth Netrapalli (NeurIPS, 2020)

Do Input Gradients Highlight Discriminative Features? - Harshay Shah; Prateek Jain 002; Praneeth Netrapalli (NeurIPS, 2021)

ModelDiff: A Framework for Comparing Learning Algorithms. - Harshay Shah; Sung Min Park; Andrew Ilyas; Aleksander Madry (ICML, 2023)

Decomposing and Editing Predictions by Modeling Model Computation. - Harshay Shah; Andrew Ilyas; Aleksander Madry (ICML, 2024)

ContextCite: Attributing Model Generation to Context. - Benjamin Cohen-Wang; Harshay Shah; Kristian Georgiev; Aleksander Madry (NeurIPS, 2024)

Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models. - Samira Abnar; Harshay Shah; Dan Busbridge; Alaaeldin Mohamed Elnouby Ali; Joshua M. Susskind; Vimal Thilak (CoRR, 2025)