The authors propose Markov chain Monte Carlo algorithms to sample from GBS distributions on unweighted graphs, and prove that it mixes in polynomial time for dense graphs. Numerical experiments on 256-vertex graphs are conducted, demonstrating that the algorithm improves the performance up to 10x.
- Yexin Zhang
- Shuo Zhou
- Tongyang Li
