Tim Reichelt
Probabilistic Programming, Probabilistic Inference
I am a PhD student at the University of Oxford lucky to be supervised by Luke Ong and Tom Rainforth as part of the AIMS Centre for Doctoral Training. I have broad interests in probabilistic machine learning, Bayesian statistics and deep learning. On a high-level, I like to build tools which help people make better data-driven decisions. More specifically, I do research in the field of probabilistic programming languages.
Publications
2023
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T. Reichelt
,
L. Ong
,
T. Rainforth
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Pitfalls of Full Bayesian Inference in Universal Probabilistic Programming, in POPL Workshop on Languages for Inference (LAFI), 2023.
2022
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T. Reichelt
,
L. Ong
,
T. Rainforth
,
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support, in Advances in Neural Information Processing Systems, 2022.
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T. Reichelt
,
A. GoliĆski
,
L. Ong
,
T. Rainforth
,
Expectation programming: Adapting probabilistic programming systems to estimate expectations efficiently, in Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, 2022.