| Regression Concept Vectors for Bidirectional Explanations in Histopathology M Graziani, V Andrearczyk, H Müller Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC …, 2018 | 131* | 2018 |
| Concept attribution: Explaining CNN decisions to physicians M Graziani, V Andrearczyk, S Marchand-Maillet, H Müller Computers in biology and medicine 123, 103865, 2020 | 74 | 2020 |
| Heterogeneous exascale computing L Hluchı, M Bobák, H Müller, M Graziani, J Maassen, H Spreeuw, ... Recent advances in intelligent engineering: volume dedicated to Imre J …, 2020 | 22* | 2020 |
| Improved interpretability for computer-aided severity assessment of Retinopathy of Prematurity M Graziani, J Brown, V Andrearczyk, V Yildiz, JP Campbell, D Erdogmus, ... SPIE Medical Imaging 2019, 2019 | 22 | 2019 |
| Megane pro: myo-electricity, visual and gaze tracking data acquisitions to improve hand prosthetics F Giordaniello, M Cognolato, M Graziani, A Gijsberts, V Gregori, G Saetta, ... 2017 International Conference on Rehabilitation Robotics (ICORR), 1148-1153, 2017 | 22 | 2017 |
| Visualizing and interpreting feature reuse of pretrained CNNs for histopathology M Graziani, V Andrearczyk, H Müller Irish Machine Vision and Image Processing Conference, 2019 | 21 | 2019 |
| A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences M Graziani, L Dutkiewicz, D Calvaresi, JP Amorim, K Yordanova, M Vered, ... Artificial intelligence review 56 (4), 3473-3504, 2023 | 18 | 2023 |
| On the Scale Invariance in State of the Art CNNs Trained on Imagenet M Graziani, T Lompech, H Müller, A Depeursinge, V Andrearczyk Machine Learning and Knowledge Extraction 3 (2), 374-391, 2021 | 15 | 2021 |
| Semi-automatic training of an object recognition system in scene camera data using gaze tracking and accelerometers M Cognolato, M Graziani, F Giordaniello, G Saetta, F Bassetto, P Brugger, ... Computer Vision Systems: 11th International Conference, ICVS 2017, Shenzhen …, 2017 | 14 | 2017 |
| Sharpening local interpretable model-agnostic explanations for histopathology: improved understandability and reliability M Graziani, I Palatnik de Sousa, MMBR Vellasco, E Costa da Silva, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 13 | 2021 |
| Interpreting intentionally flawed models with linear probes M Graziani, H Muller, V Andrearczyk Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 12 | 2019 |
| Breast histopathology with high-performance computing and deep learning M Graziani, I Eggel, F Deligand, M Bobák, V Andrearczyk, H Mueller Computing and Informatics, 2021 | 10 | 2021 |
| Interpretable CNN pruning for preserving scale-covariant features in medical imaging M Graziani, T Lompech, H Müller, A Depeursinge, V Andrearczyk Interpretable and Annotation-Efficient Learning for Medical Image Computing …, 2020 | 10 | 2020 |
| Evaluation and Comparison of CNN Visual Explanations for Histopathology M Graziani, T Lompech, H Müller, V Andrearczyk XAI workshop at AAAI21, 2021 | 8 | 2021 |
| Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs to Improve Generalization M Graziani, S Otalora, S Marchand-Maillet, H Muller, V Andrearczyk Machine Learning for Biomedical Imaging Journal 2, 2020 | 8* | 2020 |
| Shifts 2.0: Extending the dataset of real distributional shifts A Malinin, A Athanasopoulos, M Barakovic, MB Cuadra, MJF Gales, ... arXiv preprint arXiv:2206.15407, 2022 | 7 | 2022 |
| Concept discovery and dataset exploration with singular value decomposition M Graziani, A Nguyen, L O'Mahony, H Müller, V Andrearczyk ICLR 2023 Workshop on Pitfalls of limited data and computation for …, 2023 | 3 | 2023 |
| Interpretability of Deep Learning for Medical Image Classification: Improved Understandability and Generalization M Graziani University of Geneva, 2021 | 3 | 2021 |
| Tackling Bias in the Dice Similarity Coefficient: Introducing nDSC for White Matter Lesion Segmentation V Raina, N Molchanova, M Graziani, A Malinin, H Muller, MB Cuadra, ... arXiv preprint arXiv:2302.05432, 2023 | 2 | 2023 |
| Attention-based Interpretable Regression of Gene Expression in Histology M Graziani, N Marini, N Deutschmann, N Janakarajan, H Müller, ... Interpretability of Machine Intelligence in Medical Image Computing workshop …, 2022 | 2 | 2022 |
Henning MüllerProfessor in computer science at HES-SO & in radiology at the University of GenevaVerified email at hevs.ch
