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David Zimmerer

4 accepted papers

2026

CRONOS: Continuous time reconstruction for 4D medical longitudinal series

Nico Disch, Saikat Roy, Constantin Ulrich, Yannick Kirchhoff, Maximilian Rouven Rokuss, Robin Peretzke +2
ICLR 2026poster

Forecasting how 3D medical scans evolve along time is important for disease progression, treatment planning, and developmental assessment. Yet existing models either rely on a single prior scan, fixed grid times, or target global labels, which limits voxel-level forecasting under irregular sampling.…

Cited by 0Source ↗code ↗Scholar ↗
2024

Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.

Tassilo Wald, Constantin Ulrich, Priyank Jaini, Gregor Koehler, David Zimmerer, Stefan Denner +3
NeurIPS 2024poster

What representation do deep neural networks learn? How similar are images to each other for neural networks? Despite the overwhelming success of deep learning methods key questions about their internal workings still remain largely unanswered, due to their internal high dimensionality and complexity…

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2023

Why Is the Winner the Best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu D. Tizabi, Fabian Isensee, Tim J. Adler +119
CVPR 2023poster

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and…

Cited by 29Source ↗PDF ↗Scholar ↗
2021

GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data

Jens Petersen, Gregor Köhler, David Zimmerer, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein
UAI 2021poster

Neural Processes (NPs) are a family of conditional generative models that are able to model a distribution over functions, in a way that allows them to perform predictions at test time conditioned on a number of context points. A recent addition to this family, Convolutional Conditional Neural Proce…

Cited by 5Source ↗PDF ↗code ↗Scholar ↗