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Counterfactual Diffusion Models for Interpretable Morphology-based Explanations of Artificial Intelligence Models in Pathology2025 RWTH Publications (RWTH Aachen) article Computer Science Explainable Artificial Intelligence (XAI) Open access
Laura Žigutytė, Tim Lenz, Tianyu Han, Katherine J. Hewitt, Nic G. Reitsam, Sebastian Foersch, +5 more
0citations -
A Step towards Interpretable Multimodal AI Models with MultiFIX2025 Genetic and Evolutionary Computation Conference Companion (GECCO Companion) conference-paper Computer Science Explainable Artificial Intelligence (XAI) Open access
Mafalda Malafaia, Thalea Schlender, Tanja Alderliesten, Peter A. N. Bosman
0citations -
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning2023 ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) conference-paper Computer Science Evolutionary Algorithms and Applications Open access
Marco Virgolin, Eric Medvet, Tanja Alderliesten, Peter A. N. Bosman
0citations -
Counterfactual Diffusion Models for Interpretable Explanations of Artificial Intelligence Models in Pathology2024 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Explainable Artificial Intelligence (XAI) Open access
Laura Žigutytė, Tim Lenz, Tianyu Han, Katherine Jane Hewitt, Nic Gabriel Reitsam, Sebastian Foersch, +5 more
7citations -
Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts
Sarah Volinsky-Fremond, Sonali Andani, Jurriaan Barkey Wolf, Jouke Dijkstra, Sinead Melsbach, Jan J. Jobsen, +18 more
134citations -
Investigating Methods to Improve Language Model Integration for Attention-Based Encoder-Decoder ASR Models2021 Interspeech (USB) conference-paper Computer Science Speech Recognition and Synthesis Open access cited by 1 patent
Mohammad Zeineldeen, Aleksandr Glushko, Wilfried Michel, Albert Zeyer, Ralf Schlüter, Hermann Ney
38citations -
Interpretable machine learning for identifying ICU readmission risk in subgroups with probabilistic rules2025 Journal of the American Medical Informatics Association article Computer Science Machine Learning in Healthcare Open access
Lincen Yang, Siri Lise van der Meijden, M. Sesmu Arbous, Matthijs van Leeuwen
1citations -
Gradient Information and Regularization for Gene Expression Programming to Develop Data-Driven Physics Closure Models2024 Flow Turbulence and Combustion article Computer Science Evolutionary Algorithms and Applications Open access
Fabian Waschkowski, Haochen Li, Abhishek J. Deshmukh, Temistocle Grenga, Yaomin Zhao, Heinz G. Pitsch, +2 more
3citations -
Interpreting Black-box Machine Learning Models for High Dimensional Datasets2023 IEEE International Conference on Data Science and Advanced Analytics (DSAA) conference-paper Computer Science Explainable Artificial Intelligence (XAI) Open access
Md Shajalal, Alexander Graß, Till Döhmen, Sisay Adugna Chala, Alexander Boden, Christian Beecks, +1 more
19citations -
Vision-language models for chest radiography do not always need the image2026 arXiv (Cornell University) preprint Computer Science Multimodal Machine Learning Applications Open access
Mahshad Lotfinia, Sebastian Ziegelmayer, Lisa Adams, Tri-Thien Nguyen, Daniel Truhn, Andreas Maier, +1 more
0citations -
Revisiting the Relation Between Language Model Perplexity and ASR Word Error Rate for Modern End-to-End Speech Recognition2026 arXiv (Cornell University) preprint Computer Science Speech Recognition and Synthesis Open access
Mohammad Zeineldeen, Albert Zeyer, Haoran Zhang, Robin Schmitt, Ralf Schlüter, Hermann Ney
0citations