Blog Posts
Here you’ll find my latest blog posts. Do not hesitate to contact me, in case you have any feedback. You can either leave a comment under a blog or you can send me an email. Stay tuned as there are more interesting blogs in progress. Enjoy!
Random is the New Black: Real-World Position Estimation from Simulated Images
Simulation is a cheap and abundant source of data, which allows training deep neural networks on huge tailor-made datasets. Especially the ease of data labeling
Finding the Optimal Learning Rate using Bayesian Optimization
Within this blog, I am giving a short introduction into Bayesian optimization to find a near optimal learning rate. There exists a lot of great tutorials regarding the theory of Bayesian optimization. The main objective of this blog is to give a hands-on tutorial for hyperparameter optimization. As I will cover the theory only very briefly, it is recommend to read about the latter first before going through this tutorial. I am training a small ResNet implemented in PyTorch on the Kuzushiji-MNIST (or K-MNIST) dataset
Paper accepted at ICLR!
Our Paper, Time-Efficient Reinforcement Learning with Stochastic Stateful Policies, was accepted at the International Conference on Learning Representations (ICLR) 2024! We introduce a novel training
LocoMuJoCo accepted at ROL@NeurIPS
Introducing the first imitation learning benchmark tailored towards locomotion. This benchmark comes with many different environments and motion capture dataset facilitating research in locomotion. We
LS-IQ accepted at EWRL
Happy to announce that our work on Least Squares Inverse Q-Learning got accepted to the European Workshop on Reinforcement Learning.