1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.ST2025
Rebalancing Markov jump processes for non-reversible continuous-time sampling
Erik Jansson, Moritz Schauer, Ruben Seyer +1
Markov chain Monte Carlo methods are central in computational statistics, and typically rely on detailed balance to ensure invariance with respect to a target distribution. Althoug…
math.ST2024
Gradient Estimation via Differentiable Metropolis-Hastings
Gaurav Arya, Moritz Schauer, Ruben Seyer
Metropolis-Hastings estimates intractable expectations - can differentiating the algorithm estimate their gradients? The challenge is that Metropolis-Hastings trajectories are not…
stat.ML2023★ 1 cited
Differentiating Metropolis-Hastings to Optimize Intractable Densities
Gaurav Arya, Ruben Seyer, Frank Schäfer +7
We develop an algorithm for automatic differentiation of Metropolis-Hastings samplers, allowing us to differentiate through probabilistic inference, even if the model has discrete…