42 citations · 156 across the 35 of their papers we have counts for
5 papers · 1 filter
Principled Gradient-based Markov Chain Monte Carlo for Text Generation
Li Du, Afra Amini, Lucas Torroba Hennigen +4
Recent papers have demonstrated the possibility of energy-based text generation by adapting gradient-based sampling algorithms, a paradigm of MCMC algorithms that promises fast con…
Parallelising Glauber dynamics
Holden Lee
For distributions over discrete product spaces , Glauber dynamics is a Markov chain that at each step, resamples a random coordinate conditioned on the other co…
Provable benefits of score matching
Chirag Pabbaraju, Dhruv Rohatgi, Anish Sevekari +3
Score matching is an alternative to maximum likelihood (ML) for estimating a probability distribution parametrized up to a constant of proportionality. By fitting the ''score'' of…
The probability flow ODE is provably fast
Sitan Chen, Sinho Chewi, Holden Lee +3
We provide the first polynomial-time convergence guarantees for the probability flow ODE implementation (together with a corrector step) of score-based generative modeling. Our ana…
Improved Bound for Mixing Time of Parallel Tempering
Holden Lee, Zeyu Shen
In the field of sampling algorithms, MCMC (Markov Chain Monte Carlo) methods are widely used when direct sampling is not possible. However, multimodality of target distributions of…