105 citations · 108 across the 8 of their papers we have counts for
8 papers
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Chris Kolb, Tobias Weber, Bernd Bischl +1
Sparse regularization techniques are well-established in machine learning, yet their application in neural networks remains challenging due to the non-differentiability of penaltie…
Generalizing Orthogonalization for Models with Non-Linearities
David Rügamer, Chris Kolb, Tobias Weber +2
The complexity of black-box algorithms can lead to various challenges, including the introduction of biases. These biases present immediate risks in the algorithms' application. It…
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition
Tobias Weber, Jakob Dexl, David Rügamer +1
We address the computational barrier of deploying advanced deep learning segmentation models in clinical settings by studying the efficacy of network compression through tensor dec…
Post-hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings
Tobias Weber, Michael Ingrisch, Bernd Bischl +1
Purpose: To analyze and remove protected feature effects in chest radiograph embeddings of deep learning models. Methods: An orthogonalization is utilized to remove the influence o…
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction
Tobias Weber, Michael Ingrisch, Bernd Bischl +1
Undersampling is a common method in Magnetic Resonance Imaging (MRI) to subsample the number of data points in k-space, reducing acquisition times at the cost of decreased image qu…
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis
Tobias Weber, Michael Ingrisch, Bernd Bischl +1
While recent advances in large-scale foundational models show promising results, their application to the medical domain has not yet been explored in detail. In this paper, we prog…
ChatGPT Makes Medicine Easy to Swallow: An Exploratory Case Study on Simplified Radiology Reports
Katharina Jeblick, Balthasar Schachtner, Jakob Dexl +8
The release of ChatGPT, a language model capable of generating text that appears human-like and authentic, has gained significant attention beyond the research community. We expect…
Towards modelling hazard factors in unstructured data spaces using gradient-based latent interpolation
Tobias Weber, Michael Ingrisch, Bernd Bischl +1
The application of deep learning in survival analysis (SA) allows utilizing unstructured and high-dimensional data types uncommon in traditional survival methods. This allows to ad…