blog

Aug 31, 2017 How much compute do we need to train generative models?
Aug 07, 2017 My Qualifying Exam (Oral)
Jun 03, 2017 A Research to Engineering Workflow
Jun 02, 2017 ICML 2017 Workshop on Implicit Models
Feb 28, 2017 Deep and Hierarchical Implicit Models
Jan 24, 2017 Video resources for machine learning (an update)
Dec 13, 2016 On Model Mismatch and Bayesian Analysis
Oct 30, 2016 Two papers released on arXiv, "Operator Variational Inference" and "Model Criticism for Bayesian Causal Inference"
Sep 30, 2016 NIPS 2016 Workshop on Approximate Inference
Sep 19, 2016 Discussion of "Fast Approximate Inference for Arbitrarily Large Semiparametric Regression Models via Message Passing"
Aug 11, 2016 Blog has migrated from Ghost to Jekyll
Jul 21, 2016 Inference networks
Jul 03, 2016 On Bayesian and frequentist, latent variables and parameters
Jun 23, 2016 Variational auto-encoders do not train complex generative models
May 30, 2016 A quick update: Edward, and some motivations
Jan 03, 2016 Video resources for machine learning
Dec 06, 2015 Stochastic Expectation Propagation
Dec 04, 2015 At NIPS 2015
Dec 01, 2015 Denoising Criterion for Variational Auto-Encoding Framework
Nov 29, 2015 Recurrent Gaussian Processes
Nov 29, 2015 Adversarial autoencoders
Nov 28, 2015 Infinite Dimensional Word Embeddings
Nov 28, 2015 Neural Variational Inference for Text Processing
Nov 28, 2015 MuProp: Unbiased Backpropagation for Stochastic Neural Networks
Oct 12, 2015 NIPS workshop on Approximate Inference: submit your papers!
Sep 05, 2015 NIPS accepted papers are out
Sep 05, 2015 Importance weighted autoencoders
Aug 24, 2015 Random features and kernel functions
Aug 06, 2015 Survival analysis, counting processes, and Cox models
Jul 15, 2015 Trends and Highlights of ICML 2015
Jul 07, 2015 Comments on Mark Schmidt's ICML tutorial for convex optimization
Apr 27, 2015 On parameterization and natural gradients in optimization
Apr 11, 2015 On the paradigms of AI
Mar 10, 2015 The generalized method of moments (GMMs), Part I: Introduction
Feb 20, 2015 Expectation Conditional Maximization (ECM) and other variants of EM
Feb 19, 2015 Lecture notes for Reinforcement learning (CS 282r)
Nov 28, 2014 On asymptotic convergence of averaged SGD
Oct 25, 2014 Comparing elastic net to stochastic gradient descent for GLMs
Oct 05, 2014 On power law distributions, neuroscience, and bad speakers
Sep 20, 2014 Clustering with Voronoi diagrams
Sep 16, 2014 Using social media to predict outbreaks of communicable diseases
Aug 31, 2014 Welcome Week at Harvard
Aug 06, 2014 Displaying full page previews on Ghost
Jul 28, 2014 Hello world!