Adversarial Generation of Continuous Implicit Shape Representations

This article provides an overview of the paper “Adversarial Generation of Continuous Implicit Shape Representations”, which I co-authored with Matthias Fey. While the paper focuses on the theoretical aspects, I’ll provide a higher level explanation and and some visualizations here on the blog.

What I learned from building autonomous model race cars for a year

I was part of a university project group that develops autonomous model race cars. We are a group of twelve students working on the project in part time for year.

Visualizing 150000 butterflies from the Natural History Museum

Click here for the interactive visualization.

The Natural History Museum in London has a data portal in which they provide digital records for many of their specimens. Some of these records have images. I recently learned how to use machine learning tools such as convolutional neural networks and I wanted to use the NHM data to see what can be done with these tools. The dataset of butterflies seemed particularly interesting to me because the images are visually interesting, yet they are all similar in that they all contain a butterfly in a canonical pose.