| Learning and testing causal models with interventions J Acharya, A Bhattacharyya, C Daskalakis, S Kandasamy Advances in Neural Information Processing Systems 31, 2018 | 62 | 2018 |
| Learning and sampling of atomic interventions from observations A Bhattacharyya, S Gayen, S Kandasamy, A Maran, VN Variyam International Conference on Machine Learning, 842-853, 2020 | 10 | 2020 |
| Testing product distributions: A closer look A Bhattacharyya, S Gayen, S Kandasamy, NV Vinodchandran Algorithmic Learning Theory, 367-396, 2021 | 7 | 2021 |
| Efficient interventional distribution learning in the PAC framework A Bhattacharyya, S Gayen, S Kandasamy, V Raval, VN Variyam International Conference on Artificial Intelligence and Statistics, 7531-7549, 2022 | 6 | 2022 |
| Sample complexity of distinguishing cause from effect J Acharya, S Bhadane, A Bhattacharyya, S Kandasamy, Z Sun International Conference on Artificial Intelligence and Statistics, 10487-10504, 2023 | 3 | 2023 |
| Efficiently learning and sampling interventional distributions from observations A Bhattacharyya, S Gayen, S Kandasamy, A Maran, NV Vinodchandran Proceedings of the 37th International Conference on Machine Learning (ICML), 2020 | 3 | 2020 |
| Minimum intervention cover of a causal graph S Kandasamy, A Bhattacharyya, VG Honavar Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2876-2885, 2019 | 2 | 2019 |
| Tolerant testing of product distributions A Bhattacharyya, S Gayen, S Kandasamy, NV Vinodchandran Manuscript, 2019 | 1 | 2019 |
| The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models S Kandasamy, D Nagaraj arXiv preprint arXiv:2405.17068, 2024 | | 2024 |
Arnab BhattacharyyaAssociate Professor, National University of SingaporeVerified email at nus.edu.sg
