Gayen, Sutanu

11 publications

ICLR 2025 Computational Explorations of Total Variation Distance Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

NeurIPS 2025 Distribution Learning Meets Graph Structure Sampling Arnab Bhattacharyya, Sutanu Gayen, Philips George John, Sayantan Sen, N. V. Vinodchandran

AAAI 2025 Learnability of Parameter-Bounded Bayes Nets Arnab Bhattacharyya, Davin Choo, Sutanu Gayen, Dimitrios Myrisiotis

ICMLW 2024 Learnability of Parameter-Bounded Bayes Nets Arnab Bhattacharyya, Davin Choo, Sutanu Gayen, Dimitrios Myrisiotis

ICML 2024 Total Variation Distance Meets Probabilistic Inference Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

IJCAI 2023 On Approximating Total Variation Distance Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran

AISTATS 2022 Efficient Interventional Distribution Learning in the PAC Framework Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Vedant Raval, Vinodchandran N. Variyam

AISTATS 2022 Learning Sparse Fixed-Structure Gaussian Bayesian Networks Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang

ALT 2021 Testing Product Distributions: A Closer Look Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran

NeurIPS 2020 Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S Meel, N. V. Vinodchandran

ICML 2020 Learning and Sampling of Atomic Interventions from Observations Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, Vinodchandran N. Variyam