Maximilian Dreyer

According to our database, Maximilian Dreyer authored at least 9 papers between 2020 and 2024.

Collaborative distances:

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

2024

AttnLRP: Attention-Aware Layer-wise Relevance Propagation for Transformers.

Reduan Achtibat, Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Aakriti Jain, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek

CoRR, 2024

From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space.

Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

From attribution maps to human-understandable explanations through Concept Relevance Propagation.

Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

Nat. Mac. Intell., September, 2023

Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations.

Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin

CoRR, 2023

From Hope to Safety: Unlearning Biases of Deep Models by Enforcing the Right Reasons in Latent Space.

Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin

CoRR, 2023

Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models.

Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations.

Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

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

2022

From "Where" to "What": Towards Human-Understandable Explanations through Concept Relevance Propagation.

Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

CoRR, 2022

2020

ECQ^x: Explainability-Driven Quantization for Low-Bit and Sparse DNNs.

Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin

Proceedings of the xxAI - Beyond Explainable AI, 2020