Publications

For a complete list, please check my Google Scholar

2025

  1. Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting
    Marcel KolloviehMarten Lienen, David Lüdke, Leo Schwinn, and Stephan Günnemann
    The Thirteenth International Conference on Learning Representations, ICLR 2025

2024

  1. Expected Probabilistic Hierarchies
    Marcel KolloviehBertrand Charpentier, Daniel Zügner, and Stephan Günnemann
    Neural Information Processing Systems, NeurIPS 2024
  2. Assessing Robustness via Score-Based Adversarial Image Generation
    Transactions on Machine Learning Research, TMLR Nov 2024

2023

  1. Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
    Marcel Kollovieh*Abdul Fatir Ansari*, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, and Yuyang Wang
    Neural Information Processing Systems, NeurIPS 2023

2021

  1. Self-Supervised Learning from Unlabeled Fundus Photographs Improves Segmentation of the Retina
    Jan Kukačka, Anja Zenz, Marcel Kollovieh, Dominik Jüstel, and Vasilis Ntziachristos
    Medical Imaging meets NeurIPS, 2021
  2. Geometry-aware neural solver for fast Bayesian calibration of brain tumor models
    Ivan Ezhov, Tudor Mot, Suprosanna Shit, Jana Lipkova, Johannes C Paetzold, Florian Kofler, and 5 more authors
    IEEE Transactions on Medical Imaging, 2021
(*) denotes equal contribution