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Mara Graziani
Mara Graziani
IBM Research Europe & HES-SO Valais
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Titel
Zitiert von
Zitiert von
Jahr
Regression Concept Vectors for Bidirectional Explanations in Histopathology
M Graziani, V Andrearczyk, H Müller
Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC …, 2018
114*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
622020
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
222019
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
222017
Heterogeneous exascale computing
L Hluchý, M Bobák, H Müller, M Graziani, J Maassen, H Spreeuw, ...
Recent advances in intelligent engineering: volume dedicated to Imre J …, 2020
20*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
142019
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
122021
Interpreting intentionally flawed models with linear probes
M Graziani, H Muller, V Andrearczyk
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
122019
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
122017
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
92023
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
82021
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
82021
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
82020
Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs Improves Generalization
M Graziani, S Otalora, S Marchand-Maillet, H Müller, V Andrearczyk
7*2022
Evaluation and Comparison of CNN Visual Explanations for Histopathology
M Graziani, T Lompech, H Müller, V Andrearczyk
XAI workshop at AAAI21, 2021
62021
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
52022
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
22022
Interpretability of Deep Learning for Medical Image Classification: Improved Understandability and Generalization
M Graziani
University of Geneva, 2021
22021
Regression-based Deep-Learning predicts molecular biomarkers from pathology slides
OSM El Nahhas, CML Loeffler, ZI Carrero, M van Treeck, FR Kolbinger, ...
arXiv preprint arXiv:2304.05153, 2023
12023
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
12023
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