FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods

1 code implementation • ICCV 2023 • Robin Hesse, Simone Schaub-Meyer, Stefan Roth

Using our tools, we report results for 24 different combinations of neural models and XAI methods, demonstrating the strengths and weaknesses of the assessed methods in a fully automatic and systematic manner.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)

Content-Adaptive Downsampling in Convolutional Neural Networks

1 code implementation • 16 May 2023 • Robin Hesse, Simone Schaub-Meyer, Stefan Roth

Many convolutional neural networks (CNNs) rely on progressive downsampling of their feature maps to increase the network's receptive field and decrease computational cost.

Fast Axiomatic Attribution for Neural Networks

1 code implementation • NeurIPS 2021 • Robin Hesse, Simone Schaub-Meyer, Stefan Roth

Mitigating the dependence on spurious correlations present in the training dataset is a quickly emerging and important topic of deep learning.