Algorithmic trading application for use with Interactive Brokers

Python implementation of Stochastic Variational Inference for LDA

Materials for Probability Theory and Modelling

Gaussian processes (GPs) are a good choice for function approximation as they are flexible, robust to over-fitting, and provide well-calibrated predictive uncertainty. Deep Gaussian processes (DGPs) are multi-layer generalisations of GPs, but inference in these models has proved challenging. Existing approaches to inference in DGP models assume …

Python scripts to run PLS (Physical Layer Security) simulations using Cooperative Jamming techniques in V2X networks.

Solutions for the "Higher Mathematics IV - Stochastics for Engineers" course

Distributions is a web service for showing graphs of different probability distributions.

Repository for the development of the stochastics library.