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Mara Graziani
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Regression Concept Vectors for Bidirectional Explanations in Histopathology
M Graziani, V Andrearczyk, H Müller
Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC …, 2018
72*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
272020
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
182017
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
162019
Heterogeneous exascale computing
L Hluchı, M Bobák, H Müller, M Graziani, J Maassen, H Spreeuw, ...
Recent Advances in Intelligent Engineering, 81-110, 2020
13*2020
Visualizing and interpreting feature reuse of pretrained CNNs for histopathology
M Graziani, V Andrearczyk, H Müller
Irish Machine Vision and Image Processing Conference, 2019
112019
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, ...
International Conference on Computer Vision Systems, 175-184, 2017
92017
Interpreting intentionally flawed models with linear probes
M Graziani, H Muller, V Andrearczyk
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
82019
Learning Interpretable Diagnostic Features of Tumor by Multi-task Adversarial Training of Convolutional Networks: Improved Generalization
M Graziani, S Otalora, S Marchand-Maillet, H Müller, V Andrearczyk
6*2022
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
62020
Breast histopathology with high-performance computing and deep learning
M Graziani, I Eggel, V Andrearczyk
Computing and Informatics 39 (4), 780-807, 2020
52020
Process data infrastructure and data services
R Cushing, O Valkering, A Belloum, S Madougou, J Maassen, O Habala, ...
Computing and Informatics 39 (4), 724-756, 2020
42020
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
32021
Evaluation and Comparison of CNN Visual Explanations for Histopathology
M Graziani, T Lompech, H Müller, V Andrearczyk
XAI workshop at AAAI21, 2021
22021
Sharpening Local Interpretable Model-Agnostic Explanations for Histopathology: Improved Understandability and Reliability
M Graziani, I Palatnik de Sousa, MMBR Vellasco, E Costa da Silva, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2021
12021
Consistency of scale equivariance in internal representations of CNNs
V Andrearczyk, M Graziani, H Müller, A Depeursinge
Irish Machine Vision and Image Processing, 2020
12020
Interpretability of Deep Learning for Medical Image Classification: Improved Understandability and Generalization
M Graziani
University of Geneva, 2021
2021
Learning Interpretable Diagnostic Features of Tumor by Multi-task Adversarial Training of Convolutional Networks: Improved Generalization
M Graziani, S Otalora, S Marchand-Maillet, H Müller, V Andrearczyk
2020
Improved Interpretability and Generalisation for Deep Learning
M Graziani
University of Cambridge, MPhil in Machine Learning, Speech and Language …, 2017
2017
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Articles 1–19