Gutmann, Michael

1. Neural Approximate Sufficient Statistics for Implicit Models
   2020/10/20 by Chen, Yanzhi, Zhang, Dinghuai, Gutmann, Michael +2 · 9 citations
   #Applications (stat.AP) #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
2. Efficient Bayesian Experimental Design for Implicit Models
   2018/10/23 by Steven Kleinegesse, Michael U. Gutmann, Kleinegesse, Steven +1 · 5 citations
   Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Optimal Experimental Design Methods
3. Parallel Gaussian process surrogate Bayesian inference with noisy\n likelihood evaluations
   2019/05/03 by Marko Järvenpää, Järvenpää, Marko, Michael U. Gutmann +5 · 3 citations
   Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Optimal Experimental Design Methods
4. Enhanced gradient-based MCMC in discrete spaces
   2022/07/29 by Benjamin Rhodes, Rhodes, Benjamin, Michael U. Gutmann +1 · 2 citations
   Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #NMR spectroscopy and applications
5. Bregman divergence as general framework to estimate unnormalized statistical models
   2012/02/14 by Michael U. Gutmann, Gutmann, Michael, Jun-ichiro Hirayama +1 · 1 citation
   Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Mechanics and Entropy #Statistical Methods and Inference
6. Variational Noise-Contrastive Estimation
   2018/10/18 by Rhodes, Benjamin, Gutmann, Michael · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)