From the 1 of 7 linked papers with an AI index.
2 citations · 2 across the 2 of their papers we have counts for
7 papers
Explaining Temporal Graph Neural Networks via Feature-induced Information Flow
Ping Xiong, Thomas Schnake, Klaus-Robert Müller +1
The paper introduces an attribution method that explains temporal graph neural networks by quantifying information flow through both event embeddings and event-induced variables, i…
Normalized Relevance Measure as a Unifying Framework to Explain Neural Network Latent Structures
Ping Xiong, Thomas Schnake, Grégoire Montavon +2
To understand how a neural network (NN) functions and makes predictions, it has become increasingly clear that analyzing only the input domain is insufficient -- one must also exam…
Enhancing Brain Source Reconstruction by Initializing 3D Neural Networks with Physical Inverse Solutions
Marco Morik, Ali Hashemi, Klaus-Robert Müller +2
Reconstructing brain sources is a fundamental challenge in neuroscience, crucial for understanding brain function and dysfunction. Electroencephalography (EEG) signals have a high…
Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models
Khaled Kahouli, Winfried Ripken, Stefan Gugler +3
The long sampling time of diffusion models remains a significant bottleneck, which can be mitigated by reducing the number of diffusion time steps. However, the quality of samples…
Uncovering the Structure of Explanation Quality with Spectral Analysis
Johannes MaeÃ, Grégoire Montavon, Shinichi Nakajima +2
As machine learning models are increasingly considered for high-stakes domains, effective explanation methods are crucial to ensure that their prediction strategies are transparent…
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features
Thomas Schnake, Farnoush Rezaei Jafari, Jonas Lederer +5
Explainable Artificial Intelligence (XAI) plays a crucial role in fostering transparency and trust in AI systems, where traditional XAI approaches typically offer one level of abst…