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Meike Nauta
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Journal Articles
- 2023
- [j3]Meike Nauta
, Jan Trienes
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI. ACM Comput. Surv. 55(13s): 295:1-295:42 (2023) - 2022
- [j2]Olivier Paalvast, Meike Nauta, Marion Koelle, Jeroen Geerdink, Onno Vijlbrief, Johannes H. Hegeman, Christin Seifert:
Radiology report generation for proximal femur fractures using deep classification and language generation models. Artif. Intell. Medicine 128: 102281 (2022) - 2019
- [j1]Meike Nauta
Causal Discovery with Attention-Based Convolutional Neural Networks. Mach. Learn. Knowl. Extr. 1(1): 312-340 (2019)
Conference and Workshop Papers
- 2024
- [c13]Lisa Anita De Santi, Jörg Schlötterer, Meike Nauta, Vincenzo Positano, Christin Seifert:
Patch-based Intuitive Multimodal Prototypes Network (PIMPNet) for Alzheimer's Disease classification. xAI (Late-breaking Work, Demos, Doctoral Consortium) 2024: 73-80 - 2023
- [c12]Elisa Nguyen
Feature Attribution Explanations for Spiking Neural Networks. CogMI 2023: 59-68 - [c11]Meike Nauta, Jörg Schlötterer, Maurice van Keulen, Christin Seifert:
PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification. CVPR 2023: 2744-2753 - [c10]Meike Nauta
Interpreting and Correcting Medical Image Classification with PIP-Net. ECAI Workshops (1) 2023: 198-215 - [c9]Phuong Quynh Le, Meike Nauta, Van Bach Nguyen, Shreyasi Pathak, Jörg Schlötterer, Christin Seifert:
Benchmarking eXplainable AI - A Survey on Available Toolkits and Open Challenges. IJCAI 2023: 6665-6673 - [c8]Meike Nauta
The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers. xAI (1) 2023: 397-420 - 2021
- [c7]Meike Nauta, Ron van Bree, Christin Seifert:
Neural Prototype Trees for Interpretable Fine-Grained Image Recognition. CVPR 2021: 14933-14943 - [c6]Meike Nauta, Annemarie Jutte
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition. PKDD/ECML Workshops (1) 2021: 441-456 - 2020
- [c5]Meike Nauta, Michel J. A. M. van Putten, Marleen C. Tjepkema-Cloostermans, Jeroen Bos, Maurice van Keulen, Christin Seifert:
Interactive Explanations of Internal Representations of Neural Network Layers: An Exploratory Study on Outcome Prediction of Comatose Patients. KDH@ECAI 2020: 5-11 - 2019
- [c4]Michelle Peters, Lindsay Kempen, Meike Nauta, Christin Seifert:
Visualising the Training Process of Convolutional Neural Networks for Non-Experts. BNAIC/BENELEARN 2019 - [c3]Abraham Theodorus, Meike Nauta
Evaluating CNN interpretability on sketch classification. ICMV 2019: 114331Q - 2018
- [c2]Meike Nauta
LIFT: Learning Fault Trees from Observational Data. QEST 2018: 306-322 - 2017
- [c1]Meike Nauta, Mena B. Habib, Maurice van Keulen:
Detecting Hacked Twitter Accounts based on Behavioural Change. WEBIST 2017: 19-31
Informal and Other Publications
- 2024
- [i9]Lisa Anita De Santi, Jörg Schlötterer, Michael Scheschenja, Joel Wessendorf, Meike Nauta, Vincenzo Positano, Christin Seifert:
PIPNet3D: Interpretable Detection of Alzheimer in MRI Scans. CoRR abs/2403.18328 (2024) - [i8]Lisa Anita De Santi, Jörg Schlötterer, Meike Nauta, Vincenzo Positano, Christin Seifert:
Patch-based Intuitive Multimodal Prototypes Network (PIMPNet) for Alzheimer's Disease classification. CoRR abs/2407.14277 (2024) - 2023
- [i7]Meike Nauta, Johannes H. Hegeman, Jeroen Geerdink, Jörg Schlötterer, Maurice van Keulen, Christin Seifert:
Interpreting and Correcting Medical Image Classification with PIP-Net. CoRR abs/2307.10404 (2023) - [i6]Meike Nauta, Christin Seifert:
The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers. CoRR abs/2307.14517 (2023) - [i5]Una M. Kelly, Meike Nauta, Lu Liu, Luuk J. Spreeuwers, Raymond N. J. Veldhuis:
Worst-Case Morphs using Wasserstein ALI and Improved MIPGAN. CoRR abs/2310.08371 (2023) - [i4]Elisa Nguyen, Meike Nauta, Gwenn Englebienne, Christin Seifert:
Feature Attribution Explanations for Spiking Neural Networks. CoRR abs/2311.02110 (2023) - 2022
- [i3]Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, Michelle Peters, Yasmin Schmitt, Jörg Schlötterer, Maurice van Keulen, Christin Seifert:
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI. CoRR abs/2201.08164 (2022) - 2020
- [i2]Meike Nauta
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition. CoRR abs/2011.02863 (2020) - [i1]Meike Nauta, Ron van Bree, Christin Seifert:
Neural Prototype Trees for Interpretable Fine-grained Image Recognition. CoRR abs/2012.02046 (2020)
Coauthor Index
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