If I would need to reduce it to one sentence, I would describe my research interest as I am interested in Philosophy, Artificial General Intelligence and learning principles which I pursue by trying to understand the wide area of possibilities of computer science, mathematics, machine learning and Artificial Neural Networks in particular.
PyPaddle: blending graph theory and neural networks
GitHub Link: github.com/innvariant/pypaddle
PyEddy: Artifcial Landscapes for Optimization
A nice little visualization and experimenting project I am currently working on. Basically I am collecting test functions for optimization, provide additional functionality for simple visualizations of them and test various optimization strategies over them.
GitHub Link: github.com/innvariant/pyEddy
PyKlopp: repeatable model training
While the field of machine learning has a huge reproducibility problem and I am confronted with it permanently when designing new Neural Architecture Search experiments, I developed a simple binary which I am using for invoking model trainings. This is way from being finalized and currently there are lots of development efforts to make experiments repeatable.