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Gutmann Research Group (gutmanngroup)

Gutmann Research Group

gutmanngroup

Geek Repo

Repositories by the Gutmann machine learning group @ The University of Edinburgh.

Home Page:https://michaelgutmann.github.io/

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Gutmann Research Group's repositories

minebed

Source code for Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation, ICML 2020, https://arxiv.org/abs/2002.08129

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bedimplicit

Source code for "Efficient Bayesian Experimental Design for Implicit Models", AISTATS 2019, https://arxiv.org/abs/1810.09912

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demiss-vae

[TMLR] Research code for the paper "Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families".

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enhanced_discrete_gradient_mcmc

Python code for the paper “Enhanced gradient-based MCMC in discrete spaces”, TMLR 2022, https://openreview.net/forum?id=j2Mid5hFUJ

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GradBED

Code for the paper "Gradient-Based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds" https://arxiv.org/abs/2105.04379

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idad

Python code for "Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods", NeurIPS, 2021, https://proceedings.neurips.cc/paper/2021/hash/d811406316b669ad3d370d78b51b1d2e-Abstract.html

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neural-approx-ss-lfi

Python code "Neural Approximate Sufficient Statistics for Implicit Models", ICLR 2021, https://openreview.net/forum?id=SRDuJssQud

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seqbed

Code for the paper "Sequential Bayesian Experimental Design for Implicit Models via Mutual Information", Bayesian Analysis 2021, https://arxiv.org/abs/2003.09379.

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tre_code

Python code for the paper "Telescoping Density-Ratio Estimation", NeurIPS 2020

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variational-gibbs-inference

Python code for the paper "Variational Gibbs inference for statistical estimation from incomplete data", https://arxiv.org/abs/2111.13180

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VNCE

Python code for the paper "Variational Noise-Contrastive Estimation", AISTATS 2019, http://proceedings.mlr.press/v89/rhodes19a/rhodes19a.pdf

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