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I am a PhD student at University of Tübingen and the International Max Planck Research School for Intelligent Systems supervised by Robert Bamler. My PhD is funded by the Cluster of Excellence Machine Learning. I am interested in deep (probabilistic) models, flexible and efficient inference methods for large (language) models, and data compression.
If you are a Bachelor’s or Master’s student and interested in writing a thesis in our group, please reach out!

News

• December 2024: Our paper, A Note on Generalization in Variational Autoencoders: How Effective Is Synthetic Data and Overparameterization? has been accepted at TMLR following a smooth and constructive review process! Check it out if you (still) like VAEs!
• September 2024: I am excited to be joining the group of Roger Grosse for the Vector research internship in February 2025! Please reach out if you are based in the Toronto area!
• June 2024: I will present our paper at ICML 2024 and AABI 2024 in person. Chat with me in Vienna! I will also present the project at the Approximate Inference in Theory and Practice workshop in Paris!
• May 2024: Our paper Differentiable Annealed Importance Sampling Minimizes The Symmetrized Kullback-Leibler Divergence Between Initial and Target Distribution has been accepted at ICML 2024!
• November 2023: I am visiting NeurIPS 2023 in person. Talk to me in New Orleans!
• October 2023: Our paper The SVHN Dataset Is Deceptive for Probabilistic Generative Models Due to a Distribution Mismatch has been accepted at the NeurIPS 2023 Workshop on Distribution Shifts! Check out the project page!
• May 2023: I am visiting ICLR 2023 in person. Come and talk to me in Kigali, Rwanda!
• April 2023: Our paper Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers has been accepted as a TinyPaper at ICLR 2023!
• July 2022: I am starting a PhD in the group of Robert Bamler!