Bayes

Bayesian Journal Club TU Berlin

Journal Club on Bayesian inference and machine learning at TU Berlin

Next meetings and topics

The next meeting will happen the 4th of December (Wednesday) at 15:00 in MAR 4.020. The paper will be GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration https://arxiv.org/abs/1809.11165 and the moderator will be Ludwig

You can put your suggestions and vote for papers you would like to see treated in the following poll

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Suggestions

Title Person suggesting Date Link
Gaussian Process Conditional Density Estimation Theo   https://arxiv.org/abs/1810.12750

For suggestions about the organisation itself mail me

Past Topics

Date Topic Link Moderator
14th March 2018 Variational Inference with Normalizing Flows https://arxiv.org/abs/1505.05770 Florian
25th April 2018 The Generalized Reparameterization Gradient https://arxiv.org/abs/1610.02287 Théo
06th June 2018 Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm https://arxiv.org/abs/1608.04471 Dimitra
13th June 2018 Yes, but Did It Work?: Evaluating Variational Inference https://arxiv.org/abs/1802.02538 Theo
28th November 2018 Neural Processes https://arxiv.org/abs/1807.01622 Theo
19th December 2018 Neural Ordinary Differential Equations https://arxiv.org/abs/1806.07366 Florian
23rd January 2019 Semi-Implicit Variational Inference https://arxiv.org/abs/1805.11183 Christian
13th February 2019 Maximum Entropy Generators for Energy-Based Models https://arxiv.org/abs/1901.08508 Pan
11th April 2019 Rates of Convergence for Sparse Variational Gaussian Process Regression https://arxiv.org/abs/1903.03571 Theo
31st October 2019 Learning Invariances using the Marginal Likelihood https://arxiv.org/abs/1808.05563 Theo
20th November 2019 Stochastic Thermodynamics of Learning https://arxiv.org/abs/1611.09428 Cesar