Ruben Seyer
My interests lie at the intersection of Bayesian inference and machine learning, where I will work on computational methods for statistics. I am particularly interested in applications within spatial statistics and point processes. Thus far I have focused on stochastic gradient methods and piecewise deterministic Markov processes.
Showing 1 publications
Differentiating Metropolis-Hastings to Optimize Intractable Densities
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Showing 2 research projects
Fast Bayesian Inference with Piecewise Deterministic Markov Processes
Inference in the face of intractability: Bayesian applications of continuous-time Markov processes