Michael U. Gutmann
18 papers · 2012–2023 · 7 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (14) π Renaissance Researcher (7) π Interdisciplinary Bridge π£ Hot Topic Early Bird
π§
Keyword Pioneer
π£
Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(14)
π
Triple Crown
π
Keyword Champion
(3)
ποΈ
Keyword Collector
(66)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(18)
π₯
Unstoppable
(6)
β
The Questioner
Conferences
AISTATS (4)
JMLR (4)
ICML (3)
NIPS (3)
ICLR (2)
ACML (1)
CORL (1)
Top co-authors
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