activity
20112024
most citedMethods for Interpreting and Understanding Deep Neural Networks

2.8k citations · 13.3k across the 90 of their papers we have counts for

collaborators

104 papers

cs.LG2024★ 33 cited

The Clever Hans Effect in Unsupervised Learning

Jacob Kauffmann, Jonas Dippel, Lukas Ruff +3

Unsupervised learning has become an essential building block of AI systems. The representations it produces, e.g. in foundation models, are critical to a wide variety of downstream…

cs.LG2023★ 1 cited

Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation

Leander Weber, Jim Berend, Moritz Weckbecker +4

Gradient-based optimization has been a cornerstone of machine learning that enabled the vast advances of Artificial Intelligence (AI) development over the past decades. However, th…

eess.IV2023★ 9 cited

DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology

Marco Aversa, Gabriel Nobis, Miriam Hägele +10

We present DiffInfinite, a hierarchical diffusion model that generates arbitrarily large histological images while preserving long-range correlation structural information. Our app…

cs.SD2023★ 4 cited

XAI-based Comparison of Input Representations for Audio Event Classification

Annika Frommholz, Fabian Seipel, Sebastian Lapuschkin +2

Deep neural networks are a promising tool for Audio Event Classification. In contrast to other data like natural images, there are many sensible and non-obvious representations for…

cs.CV2023★ 2 cited

Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models

Frederik Pahde, Maximilian Dreyer, Wojciech Samek +1

State-of-the-art machine learning models often learn spurious correlations embedded in the training data. This poses risks when deploying these models for high-stake decision-makin…

cs.LG2023

Explainable AI for Time Series via Virtual Inspection Layers

Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon +1

The field of eXplainable Artificial Intelligence (XAI) has greatly advanced in recent years, but progress has mainly been made in computer vision and natural language processing. F…