| 2026 | CRYPTO | How Fast Does the Inverse Walk Approximate a Random Permutation? | Vishesh Jain, Tianren Liu, Clayton Mizgerd, Angelos Pelecanos, Stefano Tessaro, Vinod Vaikuntanathan |
| 2024 | SODA | Universality of Spectral Independence with Applications to Fast Mixing in Spin Glasses. | Nima Anari, Vishesh Jain, Frederic Koehler, Huy Tuan Pham, Thuy-Duong Vuong |
| 2024 | SODA | Optimal thresholds for Latin squares, Steiner Triple Systems, and edge colorings. | Vishesh Jain, Huy Tuan Pham |
| 2023 | FOCS | Optimal mixing of the down-up walk on independent sets of a given size. | Vishesh Jain, Marcus Michelen, Huy Tuan Pham, Thuy-Duong Vuong |
| 2023 | SODA | Spencer's theorem in nearly input-sparsity time. | Vishesh Jain, Ashwin Sah, Mehtaab Sawhney |
| 2022 | STOC | Entropic independence: optimal mixing of down-up random walks. | Nima Anari, Vishesh Jain, Frederic Koehler, Huy Tuan Pham, Thuy-Duong Vuong |
| 2022 | STOC | Approximate counting and sampling via local central limit theorems. | Vishesh Jain, Will Perkins, Ashwin Sah, Mehtaab Sawhney |
| 2021 | FOCS | Towards the sampling Lovsz Local Lemma. | Vishesh Jain, Huy Tuan Pham, Thuy-Duong Vuong |
| 2021 | STOC | Perfectly sampling | Vishesh Jain, Ashwin Sah, Mehtaab Sawhney |
| 2019 | COLT | Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation. | Vishesh Jain, Frederic Koehler, Jingbo Liu, Elchanan Mossel |
| 2019 | STOC | Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective. | Vishesh Jain, Frederic Koehler, Andrej Risteski |
| 2018 | COLT | The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity. | Vishesh Jain, Frederic Koehler, Elchanan Mossel |
| 2018 | COLT | The Vertex Sample Complexity of Free Energy is Polynomial. | Vishesh Jain, Frederic Koehler, Elchanan Mossel |
| 2018 | FOCS | 1-Factorizations of Pseudorandom Graphs. | Asaf Ferber, Vishesh Jain |