Marcel Kollovieh

According to our database, Marcel Kollovieh authored at least 19 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Interpolating Discrete Diffusion Models with Controllable Resampling.

Marcel Kollovieh, Sirine Ayadi, Stephan Günnemann

CoRR, April, 2026

3D Molecule Generation from Rigid Motifs via SE(3) Flows.

Roman Poletukhin, Marcel Kollovieh, Eike Eberhard, Stephan Günnemann

CoRR, January, 2026

2025

Discrete Bayesian Sample Inference for Graph Generation.

Ole Petersen, Marcel Kollovieh, Marten Lienen, Stephan Günnemann

CoRR, November, 2025

Edit-Based Flow Matching for Temporal Point Processes.

David Lüdke, Marten Lienen, Marcel Kollovieh, Stephan Günnemann

CoRR, October, 2025

Energy-Weighted Flow Matching: Unlocking Continuous Normalizing Flows for Efficient and Scalable Boltzmann Sampling.

Niclas Dern, Lennart Redl, Sebastian Pfister, Marcel Kollovieh, David Lüdke, Stephan Günnemann

CoRR, September, 2025

Byte Pair Encoding for Efficient Time Series Forecasting.

Leon Götz, Marcel Kollovieh, Stephan Günnemann, Leo Schwinn

CoRR, May, 2025

Generative Modeling with Bayesian Sample Inference.

Marten Lienen, Marcel Kollovieh, Stephan Günnemann

CoRR, February, 2025

TreeGen: A Bayesian Generative Model for Hierarchies.

Marcel Kollovieh, Nils Fleischmann, Filippo Guerranti, Bertrand Charpentier, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Efficient Time Series Processing for Transformers and State-Space Models through Token Merging.

Leon Götz, Marcel Kollovieh, Stephan Günnemann, Leo Schwinn

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Unlocking Point Processes through Point Set Diffusion.

David Lüdke, Enric Rabasseda Raventós, Marcel Kollovieh, Stephan Günnemann

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting.

Marcel Kollovieh, Marten Lienen, David Lüdke, Leo Schwinn, Stephan Günnemann

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

GeoDiffusion: A Training-Free Framework for Accurate 3D Geometric Conditioning in Image Generation.

Phillip Mueller, Talip Uenlue, Sebastian Schmidt, Marcel Kollovieh, Jiajie Fan, Stephan Günnemann, Lars Mikelsons

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

2024

Assessing Robustness via Score-Based Adversarial Image Generation.

Marcel Kollovieh, Lukas Gosch, Marten Lienen, Yan Scholten, Leo Schwinn, Stephan Günnemann

Trans. Mach. Learn. Res., 2024

Expected Probabilistic Hierarchies.

Marcel Kollovieh, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Assessing Robustness via Score-Based Adversarial Image Generation.

Marcel Kollovieh, Lukas Gosch, Yan Scholten, Marten Lienen, Stephan Günnemann

CoRR, 2023

Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting.

Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Geometry-Aware Neural Solver for Fast Bayesian Calibration of Brain Tumor Models.

Ivan Ezhov, Tudor Mot, Suprosanna Shit, Jana Lipková, Johannes C. Paetzold, Florian Kofler, Chantal Pellegrini, Marcel Kollovieh, Fernando Navarro, Hongwei Li, Marie Metz, Benedikt Wiestler, Bjoern H. Menze

IEEE Trans. Medical Imaging, 2022

U-PET: MRI-based Dementia Detection with Joint Generation of Synthetic FDG-PET Images.

Marcel Kollovieh, Matthias Keicher, Stephan Wunderlich, Hendrik Burwinkel, Thomas Wendler, Nassir Navab

CoRR, 2022

2021

Self-Supervised Learning from Unlabeled Fundus Photographs Improves Segmentation of the Retina.

Jan Kukacka, Anja Zenz, Marcel Kollovieh, Dominik Jüstel, Vasilis Ntziachristos

CoRR, 2021