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Michael Gutmann. Senior Lecturer (Associate Professor) in Machine Learning. I am a Senior Lecturer in Machine Learning at the School of Informatics of the University of Edinburgh, affiliated with the Institute for Adaptive & Neural Computation.
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Research homepage of Michael U. Gutmann, University of...
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Research homepage of Michael U. Gutmann, University of...
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Kartic Subr University of Edinburgh. Subramanian Ramamoorthy Professor of Robot Learning and Autonomy, School of Informatics, University of Edinburgh. Masashi Sugiyama Director, RIKEN Center for Advanced Intelligence Project / Professor, The University of Tokyo. Follow.
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An Extendable Python Implementation of Robust Optimisation Monte Carlo V. Gkolemis, M. Gutmann, and H. Pesonen Journal of Statistical Software 2023 @article{Gkolemis2023a, author = {Gkolemis, Vasil...Bayesian Optimization with Informative Covariance A. Eduardo, and M. Gutmann Transactions on Machine Learning Research 2023 @article{Eduardo2023a, author = {Eduardo, Afonso and Gutmann, Michael U.}...Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression A. Srivastava, S. Han, K. Xu, B. Rhodes, and M. Gutmann Transactions on Machine Learni...Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data V. Simkus, B. Rhodes, and M. Gutmann Journal of Machine Learning Research 2023 @article{Simkus2023a, author = {Simk...Pen and Paper Exercises in Machine Learning M. Gutmann University of Edinburgh 2022 @techreport{Gutmann2022b, author = {Gutmann, Michael U.}, title = {Pen and Paper Exercises in Machine Learning},...
Bayesian Optimal Experimental Design for Simulator Models of Cognition S. Valentin, S. Kleinegesse, N. Bramley, M. Gutmann, and C. Lucas In NeurIPS 2021 Workshop "AI for Science" 2021 @inproceeding...Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds S. Kleinegesse, and M. Gutmann arXiv:2105.04379 2021 @article{Kleinegesse2021a, author = {Klein...To Stir or Not to Stir: Online Estimation of Liquid Properties for Pouring Actions T. Lopez Guevara, R. Pucci, N. Taylor, M. Gutmann, S. Ramamoorthy, and K. Subr In Workshop on Learning and Inferen...Dynamic Likelihood-free Inference via Ratio Estimation (DIRE) T. Dinev, and M. Gutmann arXiv:1810.09899 2018 @article{Dinev2018, author = {Dinev, T. and Gutmann, M.U.}, journal = {arXiv:1810.09899}...Research homepage of Michael U. Gutmann, University of Edinburgh. Research topics include machine learning, approximate Bayesian inference, experimental design, energy-based models.
Michael Gutmann is a senior lecturer in machine learning in the Institute for Adaptive and Neural Computation at the School of Informatics. He previously worked at the Department of Mathematics and Statistics, and the Department of Computer Science at the University of Helsinki and Aalto University in Helsinki, Finland.
1 Introduction. Estimation of unnormalized parameterized statistical models is a computationally difficult problem. Here, we propose a new principle for estimating such models. 13th Appearing in Proceedings of the International Con-ference on Artificial Intelligence and Statistics (AISTATS) 2010, Chia Laguna Resort, Sardinia, Italy.
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Michael Gutmann. Position. Senior Lecturer in Machine Learning. Roles. Member of Institute for Adaptive and Neural Computation. Cohort Lead of MSC (Artificial Intelligence) Deputy Director of Biomedical AI CDT 2019-2027. Honours project supervision of Standard allocation.
