Meike Nauta

According to our database, Meike Nauta authored at least 18 papers between 2017 and 2024.

Collaborative distances:

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

2024

PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans.

Lisa Anita De Santi, Jörg Schlötterer, Michael Scheschenja, Joel Wessendorf, Meike Nauta, Vincenzo Positano, Christin Seifert

CoRR, 2024

Patch-based Intuitive Multimodal Prototypes Network (PIMPNet) for Alzheimer's Disease classification.

Lisa Anita De Santi, Jörg Schlötterer, Meike Nauta, Vincenzo Positano, Christin Seifert

Proceedings of the Joint Proceedings of the xAI 2024 Late-breaking Work, 2024

2023

From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI.

Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, Michelle Peters, Yasmin Schmitt, Jörg Schlötterer, Maurice van Keulen, Christin Seifert

ACM Comput. Surv., 2023

Worst-Case Morphs using Wasserstein ALI and Improved MIPGAN.

Una M. Kelly, Meike Nauta, Lu Liu, Luuk J. Spreeuwers, Raymond N. J. Veldhuis

CoRR, 2023

The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers.

Meike Nauta, Christin Seifert

Proceedings of the Explainable Artificial Intelligence, 2023

Benchmarking eXplainable AI - A Survey on Available Toolkits and Open Challenges.

Phuong Quynh Le, Meike Nauta, Van Bach Nguyen, Shreyasi Pathak, Jörg Schlötterer, Christin Seifert

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Interpreting and Correcting Medical Image Classification with PIP-Net.

Meike Nauta, Johannes H. Hegeman, Jeroen Geerdink, Jörg Schlötterer, Maurice van Keulen, Christin Seifert

Proceedings of the Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30, 2023

PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification.

Meike Nauta, Jörg Schlötterer, Maurice van Keulen, Christin Seifert

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

Feature Attribution Explanations for Spiking Neural Networks.

Elisa Nguyen, Meike Nauta, Gwenn Englebienne, Christin Seifert

Proceedings of the 5th IEEE International Conference on Cognitive Machine Intelligence, 2023

2022

Radiology report generation for proximal femur fractures using deep classification and language generation models.

Olivier Paalvast, Meike Nauta, Marion Koelle, Jeroen Geerdink, Onno Vijlbrief, Johannes H. Hegeman, Christin Seifert

Artif. Intell. Medicine, 2022

2021

This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition.

Meike Nauta, Annemarie Jutte, Jesper C. Provoost, Christin Seifert

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Neural Prototype Trees for Interpretable Fine-Grained Image Recognition.

Meike Nauta, Ron van Bree, Christin Seifert

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Interactive Explanations of Internal Representations of Neural Network Layers: An Exploratory Study on Outcome Prediction of Comatose Patients.

Meike Nauta, Michel J. A. M. van Putten, Marleen C. Tjepkema-Cloostermans, Jeroen Bos, Maurice van Keulen, Christin Seifert

Proceedings of the 5th International Workshop on Knowledge Discovery in Healthcare Data co-located with 24th European Conference on Artificial Intelligence, 2020

2019

Causal Discovery with Attention-Based Convolutional Neural Networks.

Meike Nauta, Doina Bucur, Christin Seifert

Mach. Learn. Knowl. Extr., 2019

Evaluating CNN interpretability on sketch classification.

Abraham Theodorus, Meike Nauta, Christin Seifert

Proceedings of the Twelfth International Conference on Machine Vision, 2019

Visualising the Training Process of Convolutional Neural Networks for Non-Experts.

Michelle Peters, Lindsay Kempen, Meike Nauta, Christin Seifert

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

LIFT: Learning Fault Trees from Observational Data.

Meike Nauta, Doina Bucur, Mariëlle Stoelinga

Proceedings of the Quantitative Evaluation of Systems - 15th International Conference, 2018

2017

Detecting Hacked Twitter Accounts based on Behavioural Change.

Meike Nauta, Mena B. Habib, Maurice van Keulen

Proceedings of the 13th International Conference on Web Information Systems and Technologies, 2017