Anna Hedström

According to our database, Anna Hedström authored at least 10 papers between 2022 and 2024.

Collaborative distances:

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

2024

Quanda: An Interpretability Toolkit for Training Data Attribution Evaluation and Beyond.

Dilyara Bareeva, Galip Ümit Yolcu, Anna Hedström, Niklas Schmolenski, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

CoRR, 2024

CoSy: Evaluating Textual Explanations of Neurons.

Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov

CoRR, 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

Explainable AI in grassland monitoring: Enhancing model performance and domain adaptability.

Shanghua Liu, Anna Hedström, Deepak Hanike Basavegowda, Cornelia Weltzien, Marina M.-C. Höhne

Proceedings of the 44. GIL-Jahrestagung, Informatik in der Land-, Forst- und Ernährungswirtschaft, 2024

2023

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus.

Anna Hedström, Philine Lou Bommer, Kristoffer Knutsen Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne

Trans. Mach. Learn. Res., 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

Finding the right XAI method - A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science.

Philine Lou Bommer, Marlene Kretschmer, Anna Hedström, Dilyara Bareeva, Marina M.-C. Höhne

CoRR, 2023

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

NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights.

Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022