Posts tagged PyTensor
ODE Lotka-Volterra With Bayesian Inference in Multiple Ways
- 16 January 2023
The purpose of this notebook is to demonstrate how to perform Bayesian inference on a system of ordinary differential equations (ODEs), both with and without gradients. The accuracy and efficiency of different samplers are compared.
Fitting a Reinforcement Learning Model to Behavioral Data with PyMC
- 05 August 2022
Reinforcement Learning models are commonly used in behavioral research to model how animals and humans learn, in situtions where they get to make repeated choices that are followed by some form of feedback, such as a reward or a punishment.
How to debug a model
- 02 August 2022
There are various levels on which to debug a model. One of the simplest is to just print out the values that different variables are taking on.
How to wrap a JAX function for use in PyMC
- 24 March 2022
This notebook uses libraries that are not PyMC dependencies and therefore need to be installed specifically to run this notebook. Open the dropdown below for extra guidance.