I noticed that as my personal website at my former university went down that my PhD thesis could not be found anywhere, so I'm posting it here.
During my PhD I explored how machine learning and computational modeling of the brain can be used to improve our understanding, and diagnostics …
When Osvaldo asked me to write the foreword to his new book I felt honored, excited, and a bit scared, so naturally I accepted. What follows is my best attempt to convey what makes probabilistic programming so exciting to me. Osvaldo did a great job with the book, it is …
(c) 2019 Thomas Wiecki & Ravin Kumar
As advocates of Bayesian statistics in data science we often have to convince business-minded colleagues or customers of the added value of such an approach. While there are many good reasons for applying Bayesian modeling to solve business problems (Sean J Taylor recently had …
(c) 2018 by Thomas Wiecki
Imagine you have a machine learning (ML) problem but only small data (gasp, yes, this does exist). This often happens when your data set is nested -- you might have many data points, but only few per category. For example, in ad-tech you may want predict …
(c) 2018 by Thomas Wiecki
People seemed to enjoy my intuitive and visual explanation of Markov chain Monte Carlo so I thought it would be fun to do another one, this time focused on copulas.
If you ask a statistician what a copula is they might say "a copula is …
We recently released PyMC3 3.1 after the first stable 3.0 release in January 2017. You can update either via pip install pymc3 or via conda install -c conda-forge pymc3.
A lot is happening in PyMC3-land. One thing I am particularily proud of is the developer community we have …
Download the NB: https://github.com/twiecki/WhileMyMCMCGentlySamples/blob/master/content/downloads/notebooks/random_walk_deep_net.ipynb
(c) 2017 by Thomas Wiecki -- Quantopian Inc.
Most problems solved by Deep Learning are stationary. A cat is always a cat. The rules of Go have remained stable for 2,500 years, and will likely …
(c) 2017 by Thomas Wiecki
Hierarchical models are underappreciated. Hierarchies exist in many data sets and modeling them appropriately adds a boat load of statistical power (the common metric of statistical power). I provided an introduction to hierarchical models in a previous blog post: Best Of Both Worlds: Hierarchical Linear …
(c) 2016 by Thomas Wiecki
Recently, I blogged about Bayesian Deep Learning with PyMC3 where I built a simple hand-coded Bayesian Neural Network and fit it on a toy data set. Today, we will build a more interesting model using Lasagne, a flexible Theano library for constructing various types of …
(c) 2016-2018 by Thomas Wiecki, updated by Maxim Kochurov
Original blog post: https://twiecki.github.io/blog/2016/06/01/bayesian-deep-learning/
There are currently three big trends in machine learning: Probabilistic Programming, Deep Learning and "Big Data". Inside of PP …