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Our preprint Interpolating Discrete Diffusion Models with Controllable Resampling is now available.

I joined Google as a Student Researcher in Mountain View, working on generative recommendation.

Discrete Bayesian Sample Inference for Graph Generation was accepted at ICLR 2026.

TreeGen, a Bayesian generative model for hierarchies, was accepted at NeurIPS 2025.

Efficient time series processing through token merging was accepted at ICML 2025.

Point set diffusion for unlocking point processes was accepted at ICLR 2025.

At ICLR 2025, we presented flow matching with Gaussian process priors for probabilistic time series forecasting.

Score-based adversarial image generation was published in Transactions on Machine Learning Research.

Expected Probabilistic Hierarchies was accepted at NeurIPS 2024.

Unconditional diffusion models for time series forecasting were accepted at NeurIPS 2023.

In June 2023, I started my PhD in Informatics at TUM’s Data Analytics and Machine Learning (DAML) group under the supervision of Prof. Dr. Stephan Günnemann, working on generative models for non-i.i.d. data.