Gutmann Research Group
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minebed
minebed PublicForked from stevenkleinegesse/minebed
Source code for Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation, ICML 2020, https://arxiv.org/abs/2002.08129
Python 1
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bedimplicit
bedimplicit PublicForked from stevenkleinegesse/bedimplicit
Source code for "Efficient Bayesian Experimental Design for Implicit Models", AISTATS 2019, https://arxiv.org/abs/1810.09912
Python
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GradBED
GradBED PublicForked from stevenkleinegesse/GradBED
Code for the paper "Gradient-Based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds" https://arxiv.org/abs/2105.04379
Python
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seqbed
seqbed PublicForked from stevenkleinegesse/seqbed
Code for the paper "Sequential Bayesian Experimental Design for Implicit Models via Mutual Information", Bayesian Analysis 2021, https://arxiv.org/abs/2003.09379.
Python
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tre_code
tre_code PublicForked from benrhodes26/tre_code
Python code for the paper "Telescoping Density-Ratio Estimation", NeurIPS 2020
Python
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VNCE
VNCE PublicForked from benrhodes26/VNCE
Python code for the paper "Variational Noise-Contrastive Estimation", AISTATS 2019, http://proceedings.mlr.press/v89/rhodes19a/rhodes19a.pdf
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Repositories
- demiss-vae Public Forked from vsimkus/demiss-vae
[TMLR] Research code for the paper "Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families".
gutmanngroup/demiss-vae’s past year of commit activity - variational-gibbs-inference Public Forked from vsimkus/variational-gibbs-inference
Python code for the paper "Variational Gibbs inference for statistical estimation from incomplete data", https://arxiv.org/abs/2111.13180
gutmanngroup/variational-gibbs-inference’s past year of commit activity - enhanced_discrete_gradient_mcmc Public Forked from benrhodes26/enhanced_discrete_gradient_mcmc
Python code for the paper “Enhanced gradient-based MCMC in discrete spaces”, TMLR 2022, https://openreview.net/forum?id=j2Mid5hFUJ
gutmanngroup/enhanced_discrete_gradient_mcmc’s past year of commit activity - neural-approx-ss-lfi Public Forked from cyz-ai/neural-approx-ss-lfi
Python code "Neural Approximate Sufficient Statistics for Implicit Models", ICLR 2021, https://openreview.net/forum?id=SRDuJssQud
gutmanngroup/neural-approx-ss-lfi’s past year of commit activity - idad Public Forked from desi-ivanova/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
gutmanngroup/idad’s past year of commit activity - tre_code Public Forked from benrhodes26/tre_code
Python code for the paper "Telescoping Density-Ratio Estimation", NeurIPS 2020
gutmanngroup/tre_code’s past year of commit activity - GradBED Public Forked from stevenkleinegesse/GradBED
Code for the paper "Gradient-Based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds" https://arxiv.org/abs/2105.04379
gutmanngroup/GradBED’s past year of commit activity - minebed Public Forked from stevenkleinegesse/minebed
Source code for Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation, ICML 2020, https://arxiv.org/abs/2002.08129
gutmanngroup/minebed’s past year of commit activity - VNCE Public Forked from benrhodes26/VNCE
Python code for the paper "Variational Noise-Contrastive Estimation", AISTATS 2019, http://proceedings.mlr.press/v89/rhodes19a/rhodes19a.pdf
gutmanngroup/VNCE’s past year of commit activity - bedimplicit Public Forked from stevenkleinegesse/bedimplicit
Source code for "Efficient Bayesian Experimental Design for Implicit Models", AISTATS 2019, https://arxiv.org/abs/1810.09912
gutmanngroup/bedimplicit’s past year of commit activity
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