23 citations · 29 across the 9 of their papers we have counts for
9 papers
Patch-based Intuitive Multimodal Prototypes Network (PIMPNet) for Alzheimer's Disease classification
Lisa Anita De Santi, Jörg Schlötterer, Meike Nauta +2
Volumetric neuroimaging examinations like structural Magnetic Resonance Imaging (sMRI) are routinely applied to support the clinical diagnosis of dementia like Alzheimer's Disease…
Feature importance to explain multimodal prediction models. A clinical use case
Jorn-Jan van de Beld, Shreyasi Pathak, Jeroen Geerdink +2
Surgery to treat elderly hip fracture patients may cause complications that can lead to early mortality. An early warning system for complications could provoke clinicians to monit…
A Second Look on BASS -- Boosting Abstractive Summarization with Unified Semantic Graphs -- A Replication Study
Osman Alperen Koraş, Jörg Schlötterer, Christin Seifert
We present a detailed replication study of the BASS framework, an abstractive summarization system based on the notion of Unified Semantic Graphs. Our investigation includes challe…
The Queen of England is not England's Queen: On the Lack of Factual Coherency in PLMs
Paul Youssef, Jörg Schlötterer, Christin Seifert
Factual knowledge encoded in Pre-trained Language Models (PLMs) enriches their representations and justifies their use as knowledge bases. Previous work has focused on probing PLMs…
Feature Attribution Explanations for Spiking Neural Networks
Elisa Nguyen, Meike Nauta, Gwenn Englebienne +1
Third-generation artificial neural networks, Spiking Neural Networks (SNNs), can be efficiently implemented on hardware. Their implementation on neuromorphic chips opens a broad ra…
Know What Not To Know: Users' Perception of Abstaining Classifiers
Andrea Papenmeier, Daniel Hienert, Yvonne Kammerer +2
Machine learning systems can help humans to make decisions by providing decision suggestions (i.e., a label for a datapoint). However, individual datapoints do not always provide e…