Meike Nauta

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

Maurice van Keulen, Christin Seifert, Michel J. A. M. van Putten, 2020, KDH@ECAI.

Causal Discovery with Attention-Based Convolutional Neural Networks

Doina Bucur, Christin Seifert, Meike Nauta, 2019, Mach. Learn. Knowl. Extr..

LIFT: Learning Fault Trees from Observational Data

Doina Bucur, Mariëlle Stoelinga, Meike Nauta, 2018, QEST.

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

Christin Seifert, Meike Nauta, Michelle Peters, 2019, BNAIC/BENELEARN.

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

Christin Seifert, Meike Nauta, Jesper Provoost, 2020, ArXiv.

Neural Prototype Trees for Interpretable Fine-grained Image Recognition pdf

Christin Seifert, Meike Nauta, Ron van Bree, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Detecting Hacked Twitter Accounts based on Behavioural Change

Maurice van Keulen, Meike Nauta, Mena B. Habib, 2017, WEBIST.

Evaluating CNN interpretability on sketch classification

Abraham Theodorus, Meike Nauta, Christin Seifert, 2020, International Conference on Machine Vision.

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

Christin Seifert, Maurice van Keulen, Meike Nauta, 2022 .

Neural Prototype Trees for Interpretable Fine-grained Image Recognition

Christin Seifert, Meike Nauta, Ron van Bree, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).