I published my post on the relAI blog: "Using topological features to prevent topological errors"

My blogpost on persistent homology for machine learning, based on the line of research I had the chance to contribute to in my master’s thesis, was posted on the relAI blog:

Read the blogpost at the relAI blog

The post is an easy-to-parse introduction to the basic concepts of topological data analysis (persistent homology), namely what it intuitively means to identify topological features in images and measure their persistence over a range of brightness values. The relAI (short for the Konrad Zuse School of Excellence in Reliable AI) blog publishes post by the master and PhD students supported by the relAI program about their reliable AI research.