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Sep 24, 2024 · Michael U. Gutmann. I am a Senior Lecturer (Assoc Prof) in Machine Learning at the School of Informatics of the University of Edinburgh, affiliated with the Institute for Adaptive & Neural Computation. My research is in machine learning for science, with a focus on developing methods for (Bayesian) inference and design.
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Improving Variational Autoencoder Estimation from Incomplete...
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Sep 24, 2024 · Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational FamiliesV. Simkus, M. U. Gutmann, Transactions on Machine Learning Research (TMLR), 2024 [url] [arxiv] Designing optimal behavioral experiments using machine learningS.
2017. Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models. MU Gutmann, J Corander. Journal of Machine Learning Research 17, 1-47. , 2016. 350. 2016. Fundamentals and recent developments in approximate Bayesian computation. J Lintusaari, MU Gutmann, R Dutta, S Kaski, J Corander.
Semantic Scholar profile for Michael U Gutmann, with 598 highly influential citations and 99 scientific research papers.
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M. U. Gutmann University of Edinburgh 2022. Courses at the University of Edinburgh. 2023/24 ... CC BY-SA 4.0 Michael U. Gutmann. Last modified: September 24, 2024.
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Speaker: Professor Michael Gutmann. Biography: Michael Gutmann is faculty in machine learning at the School of Informatics at the University of Edinburgh. He holds MSc degrees from ETH Zurich and Ecole Centrale Paris, and a PhD degree in computational neuroscience from the University of Tokyo.