| May 26 2021 |
Variational Learning of Inducing Variables in Sparse Gaussian Processes, Michalis Titsias, 2009 |
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| April 26 2021 |
Bayesian Gaussian Process Latent Variable Model, Michalis Titsias and Neil Lawrence, 2010 |
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| March 29 2021 |
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models, Neil Lawrence, 2005 |
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| March 15 2021 |
The mathematics of UMAP, Adele Jackson, 2019 |
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| March 2 2021 |
Diffusion maps, Coifman and Lafon, 2006 |
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| Feb 9 2021 |
A Global Geometric Framework for Nonlinear Dimensionality Reduction, Tenenbaum et al, 2000 |
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| January 12 2021 |
Neural Ordinary Differential Equations, Chen et al, 2018 |
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| December 15 2020 |
Variational Boosting: Iteratively Refining Posterior Approximations, Miller et al, 2017 |
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| December 1 2020 |
Automatic Differentiation in Machine Learning: a Survey, Baydin et al, 2018 |
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| November 17 2020 |
Covariances, Robustness, and Variational Bayes, Giordano et al, 2018 |
Martin? |
| November 3 2020 |
Chapter 4.3 Expectation-Propagation Algorithms of Graphical Models, Exponential Families, and Variational Inference, Wainwright and Jordan, 2008 |
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| October 20 2020 |
Chapter 4.1 Sum-Product and Bethe Approximation of Graphical Models, Exponential Families, and Variational Inference, Wainwright and Jordan, 2008 |
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| October 6 2020 |
Chapter 3 Graphical Models as Exponential Families of Graphical Models, Exponential Families, and Variational Inference, Wainwright and Jordan, 2008 |
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| September 22 2020 |
Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server, Hasenclever et al, 2017 |
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| September 7 2020 |
Expectation propagation as a way of life: A framework for Bayesian inference on partitioned data, Vehtari et al, 2019 |
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| August 24 2020 |
Expectation Propagation for Approximate Bayesian Inference, Thomas P Minka, 2001 |
Martin |
| August 10 2020 |
VAE with a VampPrior, Tomczak and Welling, 2018 |
Yong See |
| July 27 2020 |
BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders, Märtens and Yau, 2020 |
Heejung |
| July 13 2020 |
Composing graphical models with neural networks for structured representations and fast inference, Johnson et al, 2016 |
Martin |
| July 6 2020 |
A Unifying Review of Linear Gaussian Models, Roweis and Ghahramani, 1999 |
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| June 15, 29 2020 |
Particle Markov chain Monte Carlo methods, Andrieu et al, 2010 |
Heejung/Martin |
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An Introduction to Sequential Monte Carlo Methods, Doucet et al, 2001 |
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| June 9 2020 |
Bayesian posterior sampling via stochastic gradient fisher scoring, Ahn et al, 2012 |
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| May 25 2020 |
Bayesian Computing with INLA: A Review, Rue et al, 2017 |
Martin |
| May 18 2020 |
A Complete Recipe for Stochastic Gradient MCMC, Ma et al, 2015 |
Heejung |
| May 11 2020 |
Bayesian Learning via Stochastic Gradient Langevin Dynamics, Welling and Teh, 2011 |
Heejung |
| May 4 2020 |
Unbiased Implicit Variational Inference, Titsias and Ruiz, 2019 |
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| April 27 2020 |
Stochastic Gradient Descent as Approximate Bayesian Inference, Mandt et al, 2017 |
Martin |
| April 20 2020 |
A Survey of Optimization Methods from a Machine Learning Perspective, Sun et al, 2019 |
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| April 14 2020 |
An overview of gradient descent optimization algorithms, Sebastian Ruder, 2017 and/or this blog |
Qiuyi |
| March 30 2020 |
Tutorial on Variational Autoencoders, CARL DOERSCH, 2016 and What is a variational autoencoder? |
Hui |
| March 9 2020 |
Automatic Differentiation Variational Inference, Kucukelbir et al, 2017 |
Anubhav |
| March 4 and 9 2020 |
Martin's presentation: Scalable Multi-output Gaussian Processes |
Martin |
| March 2 2020 |
Black Box Variational Inference, Ranganath et al, 2014 and Video: presentation by David Blei |
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| Feb 17 2020 |
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo, Hoffman and Gelman, 2014 |
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| Feb 3 2020 |
MCMC using Hamiltonian dynamics, Radford M. Neal, 2012 and Video on HMC |
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| Jan 20 2020 |
Scaling probabilistic models of genetic variation to millions of humans, Gopalan et al, 2016 |
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| Jan 13 2020 |
Stochastic Variational Inference, Hoffman et al, 2013 |
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| Dec 13 2019 |
Analysis of Population Structure: A Unifying Framework and Novel Methods Based on Sparse Factor Analysis, Engelhardt and Stephens, 2010 |
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| Nov 5 and 20 2019 |
fastSTRUCTURE: Variational Inference of Population fStructure in Large SNP Data Sets, Raj et al, 2014 |
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| Oct 30 2019 |
Inference of Population Structure Using Multilocus Genotype Data, Pritchard et al, 2000 |
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| Oct 15 2019 |
Empirical Bayes Matrix Factorization, Wang and Stephens, 2018 |
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| Oct 8 2019 |
Variational Inference: A Review for Statisticians, Blei et al, 2017 - Implementation of VI algorithm |
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| Sept 17 2019 |
Variational Inference: A Review for Statisticians, Blei et al, 2017 - Derivation of VI algorithm |
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| Aug 27 2019 |
Variational Inference: A Review for Statisticians, Blei et al, 2017 |
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