Approximate counting and sampling via local central limit theorems

Author:

Jain Vishesh1,Perkins Will2,Sah Ashwin3,Sawhney Mehtaab3

Affiliation:

1. Stanford University, USA

2. University of Illinois at Chicago, USA

3. Massachusetts Institute of Technology, USA

Publisher

ACM

Reference45 articles.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Parameter estimation for Gibbs distributions;ACM Transactions on Algorithms;2024-07-30

2. Towards derandomising Markov chain Monte Carlo;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06

3. Optimal mixing of the down-up walk on independent sets of a given size;2023 IEEE 64th Annual Symposium on Foundations of Computer Science (FOCS);2023-11-06

4. Approximately Counting Independent Sets of a Given Size in Bounded-Degree Graphs;SIAM Journal on Computing;2023-04-26

5. Absence of zeros implies strong spatial mixing;Probability Theory and Related Fields;2023-02-03

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