Python

Bayesian-Inference

Gaussian Process Regression

This post introduces the theory underpinning Gaussian process regression and provides a basic walk-through in python.

Aidan Scannell

• 1 Oct, 2019 • 22 min read

Gaussian-Processes

Probabilistic Modelling

I am in the process of creating Jupyter notebooks for several probabilistic models (Bayesian linear regression, Gaussian process regression) and approximate inference algorithms. …

Aidan Scannell

• 13 Mar, 2019 • 1 min read

Gaussian-Processes

Model-Based Reinforcement Learning with Gaussian Processes

In this work I re-implemented the PILCO algorithm in python using Tensorflow and GPflow. This work was mainly carried out for personal development and some of the implementation is …

Aidan Scannell

• 13 Mar, 2019 • 1 min read

Approximate-Inference

Approximate Inference

This work implements and compares a variety of approximate inference techniques for the tasks of image de-noising (restoration) and image segmentation.

Aidan Scannell

• 13 Mar, 2019 • 1 min read

Amazon Picking Challenge

As part of the FARSCOPE CDT program I worked in a team to develop a solution to Amazon’s picking challenge. This involved designing a robotic pick-and-place system that was capable …

26 Apr, 2018 • 2 min read