25 citations · 25 across the 1 of their papers we have counts for
8 papers
Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization
Rohan Reddy Mekala, Frederik Pahde, Simon Baur +11
In the realm of dermatological diagnoses, where the analysis of dermatoscopic and microscopic skin lesion images is pivotal for the accurate and early detection of various medical…
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression
Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde +2
Deep Neural Networks are prone to learning and relying on spurious correlations in the training data, which, for high-risk applications, can have fatal consequences. Various approa…
PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits
Maximilian Dreyer, Erblina Purelku, Johanna Vielhaben +2
The field of mechanistic interpretability aims to study the role of individual neurons in Deep Neural Networks. Single neurons, however, have the capability to act polysemantically…
Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test
Anna Hedström, Leander Weber, Sebastian Lapuschkin +1
The Model Parameter Randomisation Test (MPRT) is widely acknowledged in the eXplainable Artificial Intelligence (XAI) community for its well-motivated evaluative principle: that th…
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…
Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models
Daniel G. Krakowczyk, Paul Prasse, David R. Reich +3
Recent work in XAI for eye tracking data has evaluated the suitability of feature attribution methods to explain the output of deep neural sequence models for the task of oculomotr…