← Authors

Michael U. Gutmann

18 papers · 2012–2023 · 7 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (7) 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (11) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (14) πŸ‘‘ Triple Crown πŸ† Keyword Champion (3) πŸ—ƒοΈ Keyword Collector (66) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (18) πŸ”₯ Unstoppable (6) ❓ The Questioner

Conferences

AISTATS (4) JMLR (4) ICML (3) NIPS (3) ICLR (2) ACML (1) CORL (1)

Top co-authors

Steven Kleinegesse (3) Benjamin Rhodes (3) Yanzhi Chen (3) Kai Xu (2) Aapo HyvΓ€rinen (2) Akash Srivastava (2) Jukka Corander (2) Charles Sutton (2) Tatiana Lopez-Guevara (1) Pekka Marttinen (1)

Keywords

likelihood-free inference (5) bayesian inference (4) mutual information (3) implicit model (3) approximate bayesian computation (3) variational inference (3) noise-contrastive estimation (3) partition function (2) unnormalised model (2) neural network (2) bayesian experimental design (2) bayesian optimization (2) generative model (2) posterior distribution (1) statistical independence (1) deep learning (1) independent component analysis (1) representation learning (1) parameter estimation (1) experimental design (1)

Papers

Is Learning Summary Statistics Necessary for Likelihood-free Inference? ICML 2023
Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data JMLR 2023
Neural Approximate Sufficient Statistics for Implicit Models ICLR 2021
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods NIPS 2021
Generative Ratio Matching Networks ICLR 2020
Telescoping Density-Ratio Estimation NIPS 2020
Robust Optimisation Monte Carlo AISTATS 2020
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation ICML 2020
Variational Noise-Contrastive Estimation AISTATS 2019
Adaptive Gaussian Copula ABC AISTATS 2019
Efficient Bayesian Experimental Design for Implicit Models AISTATS 2019
ELFI: Engine for Likelihood-Free Inference JMLR 2018
Conditional Noise-Contrastive Estimation of Unnormalised Models ICML 2018
Adaptable Pouring: Teaching Robots Not to Spill using Fast but Approximate Fluid Simulation CORL 2017
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning NIPS 2017
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models JMLR 2016
Topographic Analysis of Correlated Components ACML 2012
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics JMLR 2012