Research

My research interests are broadly in the areas of:

Topological Data Analysis: Statistical behavior of Betti numbers, statistical inference from topological summaries, robust topological inference
Statistical Learning Theory: Reproducing kernel Hilbert spaces in probability and statistics, differential privacy
Probabilistic Methods: Hamiltonian Monte Carlo, generative models

The following is a list of my publications and preprints.

Repelling-Attracting Hamiltonian Monte Carlo

Siddharth Vishwanath, Hyungsuk Tak
Submitted. (2024) [arXiv], [code]

Efficient and Outlier Robust Topological Inference

Siddharth Vishwanath, Bharath Sriperumbudur, Kenji Fukumizu, and Satoshi Kuriki
Submitted. (2022) [arXiv], [code]

On the limits of Topological Data Analysis for Statistical Inference

Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, and Bharath Sriperumbudur
Submitted. (2022) [arXiv], [Slides], [Talk]

Monolith Soil Core Sampling to Develop Nitrate Testing Protocol for Manure Injection

Robert J. Meinen, Douglas B. Beegle, Siddharth Vishwanath, Peter J. A. Kleinman, Louis S. Saporito, John Spargo, Heather Karsten, Justin Dillon
Soil Science Society of America Journal. Springer. (2022) [Link]

The Shape of Edge Differential Privacy

Siddharth Vishwanath, Jonathan Hehir
Theory and Practice of Differential Privacy Workshop, ICML. (2021) [Poster], [Workshop Paper]

Robust Persistence Diagrams using Reproducing Kernels

Siddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, and Bharath Sriperumbudur
Advances in Neural Information Processing Systems. NeurIPS. (2021) [Link], [Slides], [Code], [Poster]

Bayesian Inference and Optimal Censoring Scheme under Progressive Censoring

Siddharth Vishwanath, Debasis Kundu
Advances in Reliability and System Engineering. Springer. (2017) [Link]