5 citations · 7 across the 5 of their papers we have counts for
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stat.CO2024
Automated Techniques for Efficient Sampling of Piecewise-Deterministic Markov Processes
Charly Andral, Kengo Kamatani
Piecewise deterministic Markov processes (PDMPs) are a class of continuous-time Markov processes that were recently used to develop a new class of Markov chain Monte Carlo algorith…
stat.CO2024
Combining Normalizing Flows and Quasi-Monte Carlo
Charly Andral
Recent advances in machine learning have led to the development of new methods for enhancing Monte Carlo methods such as Markov chain Monte Carlo (MCMC) and importance sampling (IS…
stat.CO2022★ 5 cited
The Importance Markov Chain
Charly Andral, Randal Douc, Hugo Marival +1
The Importance Markov chain is a novel algorithm bridging the gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based…