Michael U. Gutmann
18 papers · 2012–2023 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (28) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Champion
(6)
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Triple Crown
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Deep Specialist
(11)
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Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
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The Questioner
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Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
ποΈ
Keyword Collector
(69)
Top co-authors
Research topics
Machine Learning
(17)
Optimization & Theory
(15)
Artificial Intelligence
(9)
Deep Learning
(7)
Bayesian & Probabilistic
(7)
Models
(6)
Core Methods
(5)
Learning Types Β· Machine Learning
(4)
Learning Types Β· Deep Learning
(3)
Mathematics & Optimization
(2)
Core AI
(2)
Learning Paradigms
(2)
Optimization
(2)
Computer Vision
(1)
Interdisciplinary
(1)
Keywords
likelihood-free inference
(6)
implicit model
(4)
mutual information
(4)
variational inference
(4)
approximate bayesian computation
(4)
bayesian inference
(4)
generative model
(3)
noise contrastive estimation
(3)
neural network
(3)
sufficient statistics
(2)
unnormalised model
(2)
partition function
(2)
bayesian experimental design
(2)
bayesian optimization
(2)
statistical independence
(1)
deep learning
(1)
independent component analysis
(1)
parameter estimation
(1)
representation learning
(1)
visual cortex
(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
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods
NeurIPS 2021
Neural Approximate Sufficient Statistics for Implicit Models
ICLR 2021
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation
ICML 2020
Generative Ratio Matching Networks
ICLR 2020
Robust Optimisation Monte Carlo
AISTATS 2020
Telescoping Density-Ratio Estimation
NeurIPS 2020
Adaptive Gaussian Copula ABC
AISTATS 2019
Efficient Bayesian Experimental Design for Implicit Models
AISTATS 2019
Variational Noise-Contrastive Estimation
AISTATS 2019
Conditional Noise-Contrastive Estimation of Unnormalised Models
ICML 2018
ELFI: Engine for Likelihood-Free Inference
JMLR 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
NeurIPS 2017
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models
JMLR 2016
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
JMLR 2012
Topographic Analysis of Correlated Components
ACML 2012