Demetri Pananos

Demetri Pananos

Biostatistics Ph.D Candidate at Western University.

Rat Tumors and PyMC3

less than 1 minute read

Published:

I’m very proud to say I have contributed this example to PyMC3’s documentation. It details how to compute posterior means for Gelman’s rat tumour example in BDA3.

Hoping to contribute more material to the library in the future.q

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GSoC 2019: Gradient Descent for ODEs (But This Time, In Theano)

7 minute read

Published:

A little while ago, I wrote a post on doing gradient descent for ODEs. In that post, I used autograd to do the automatic differentiation. While neat, it was really a way for me to get familiar with some math that I was to use for GSoC. After taking some time to learn more about theano, I’ve reimplemented the blog post, this time using theano to perform the automatic differentiation. If you’re read the previous post, then skip right to the code.

Gradient Descent for ODEs

7 minute read

Published:

Gradient descent usually isn’t used to fit Ordinary Differential Equations (ODEs) to data (at least, that isn’t how the Applied Mathematics departments to which I have been a part have done it). Nevertheless, that doesn’t mean that it can’t be done. For some of my recent GSoC work, I’ve been investigating how to compute gradients of solutions to ODEs without access to the solution’s analytical form. In this blog post, I describe how these gradients can be computed and how they can be used to fit ODEs to synchronous data with gradient descent.

GSoC 2019: ODE Inception

5 minute read

Published:

Let’s take stock of exactly where we are in this journey it implement HMC for differential equations.