Leander Weber

According to our database, Leander Weber authored at least 12 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test.

Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina M.-C. Höhne

CoRR, 2024

A Fresh Look at Sanity Checks for Saliency Maps.

Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina M.-C. Höhne

Proceedings of the Explainable Artificial Intelligence, 2024

2023

Beyond explaining: Opportunities and challenges of XAI-based model improvement.

Leander Weber, Sebastian Lapuschkin, Alexander Binder, Wojciech Samek

Inf. Fusion, April, 2023

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond.

Anna Hedström, Leander Weber, Daniel Krakowczyk, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne

J. Mach. Learn. Res., 2023

Layer-wise Feedback Propagation.

Leander Weber, Jim Berend, Alexander Binder, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

CoRR, 2023

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations.

Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Finding and removing Clever Hans: Using explanation methods to debug and improve deep models.

Christopher J. Anders, Leander Weber, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin

Inf. Fusion, 2022

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations.

Anna Hedström, Leander Weber, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne

CoRR, 2022

PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging.

Frederik Pahde, Leander Weber, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin

CoRR, 2022

Measurably Stronger Explanation Reliability Via Model Canonization.

Franz Motzkus, Leander Weber, Sebastian Lapuschkin

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI.

Sami Ede, Serop Baghdadlian, Leander Weber, An Nguyen, Dario Zanca, Wojciech Samek, Sebastian Lapuschkin

Proceedings of the Machine Learning and Knowledge Extraction, 2022

2020

Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution.

Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder

Proceedings of the 25th International Conference on Pattern Recognition, 2020