Learning and Testing Causal Models with Interventions. - Jayadev Acharya; Arnab Bhattacharyya 001; Constantinos Daskalakis; Saravanan Kandasamy 002 (NeurIPS, 2018)

Minimum Intervention Cover of a Causal Graph. - Saravanan Kandasamy 002; Arnab Bhattacharyya 001; Vasant G. Honavar (AAAI, 2019)

Learning and Sampling of Atomic Interventions from Observations. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Ashwin Maran; N. Variyam Vinodchandran (ICML, 2020)

Efficiently Learning and Sampling Interventional Distributions from Observations. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Ashwin Maran; N. V. Vinodchandran (CoRR, 2020)

Testing Product Distributions: A Closer Look. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; N. V. Vinodchandran (ALT, 2021)

Efficient inference of interventional distributions. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Vedant Raval; N. V. Vinodchandran (CoRR, 2021)

Efficient interventional distribution learning in the PAC framework. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Vedant Raval; N. Variyam Vinodchandran (AISTATS, 2022)

Sample Complexity of Distinguishing Cause from Effect. - Jayadev Acharya; Sourbh Bhadane; Arnab Bhattacharyya 001; Saravanan Kandasamy 002; Ziteng Sun (AISTATS, 2023)

The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models. - Saravanan Kandasamy 002; Dheeraj Nagaraj (NeurIPS, 2024)