Graph Learning for Inverse Landscape Genetics. - Prathamesh Dharangutte; Christopher Musco (AAAI, 2021)

Dynamic Trace Estimation. - Prathamesh Dharangutte; Christopher Musco (NeurIPS, 2021)

An Energy-Based View of Graph Neural Networks. - John Y. Shin; Prathamesh Dharangutte (CoRR, 2021)

Integer Subspace Differential Privacy. - Prathamesh Dharangutte; Jie Gao 001; Ruobin Gong; Fang-Yi Yu (AAAI, 2023)

HeartInsightify: Interpreting Longitudinal Heart Rate Data for Health Insights through Conformal Clustering. - Prathamesh Dharangutte; Zongxing Xie; Jie Gao 001; Elinor Schoenfeld; Yindong Hua; Fan Ye 003 (BIBM, 2023)

A Tight Analysis of Hutchinson's Diagonal Estimator. - Prathamesh Dharangutte; Christopher Musco (SOSA, 2023)

Learning-Augmented Maximum Independent Set. - Vladimir Braverman; Prathamesh Dharangutte; Vihan Shah; Chen Wang 027 (APPROX/RANDOM, 2024)

Metric Clustering and MST with Strong and Weak Distance Oracles. - MohammadHossein Bateni; Prathamesh Dharangutte; Rajesh Jayaram; Chen Wang (COLT, 2024)

Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time. - Vladimir Braverman; Prathamesh Dharangutte; Shreyas Pai; Vihan Shah; Chen Wang 027 (AISTATS, 2025)

Differentially Private Range Queries with Correlated Input Perturbation. - Prathamesh Dharangutte; Jie Gao 001; Ruobin Gong; Guanyang Wang (AISTATS, 2025)

Hardness and Approximation Algorithms for Balanced Districting Problems. - Prathamesh Dharangutte; Jie Gao 001; Shang-En Huang; Fang-Yi Yu (FORC, 2025)

Relative Error Fair Clustering in the Weak-Strong Oracle Model. - Vladimir Braverman; Prathamesh Dharangutte; Shaofeng H.-C. Jiang; Hoai-An Nguyen; Chen Wang 027; Yubo Zhang; Samson Zhou (CoRR, 2025)