| FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents G Jaume, HK Ekenel, JP Thiran International Conference on Document Analysis and Recognition Workshops …, 2019 | 80 | 2019 |
| Hact-net: A hierarchical cell-to-tissue graph neural network for histopathological image classification P Pati, G Jaume, LA Fernandes, A Foncubierta-Rodríguez, F Feroce, ... Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2020 | 24 | 2020 |
| Quantifying explainers of graph neural networks in computational pathology G Jaume, P Pati, B Bozorgtabar, A Foncubierta, AM Anniciello, F Feroce, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 22 | 2021 |
| Towards explainable graph representations in digital pathology G Jaume, P Pati, A Foncubierta-Rodriguez, F Feroce, G Scognamiglio, ... ICML workshop on Computational Biology, 2020 | 20 | 2020 |
| Hierarchical Graph Representations in Digital Pathology P Pati, G Jaume, A Foncubierta, F Feroce, AM Anniciello, G Scognamiglio, ... Medical Image Analysis, 2021 | 14 | 2021 |
| HistoCartography: A Toolkit for Graph Analytics in Digital Pathology G Jaume, P Pati, V Anklin, A Foncubierta, M Gabrani MICCAI workshop on on Computational Pathology (COMPAY), 2021 | 9 | 2021 |
| Method and system for extracting information from an image of a filled form document AF Rodriguez, M Gabrani, G Jaume US Patent 10,769,425, 2020 | 6 | 2020 |
| Interpreting data from scanned tables W Farrukh, A Foncubierta-Rodriguez, AN Ciubotaru, G Jaume, C Bejas, ... 2017 14th IAPR International Conference on Document Analysis and Recognition …, 2017 | 6 | 2017 |
| Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs V Anklin, P Pati, G Jaume, B Bozorgtabar, A Foncubierta-Rodríguez, ... MICCAI, 2021 | 5 | 2021 |
| Hierarchical Cell-to-Tissue graph representations for breast cancer subtyping in digital pathology P Pati, G Jaume, A Foncubierta, F Feroce, AM Anniciello, G Scognamiglio, ... arXiv preprint arXiv:2102.11057, 2021 | 3 | 2021 |
| edGNN: a Simple and Powerful GNN for Directed Labeled Graphs G Jaume, A Nguyen, MR Martínez, JP Thiran, M Gabrani arXiv preprint arXiv:1904.08745, 2019 | 3 | 2019 |
| Bracs: A dataset for breast carcinoma subtyping in h&e histology images N Brancati, AM Anniciello, P Pati, D Riccio, G Scognamiglio, G Jaume, ... arXiv preprint arXiv:2111.04740, 2021 | 2 | 2021 |
| Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks G Jaume, B Bozorgtabar, HK Ekenel, JP Thiran, M Gabrani arXiv preprint arXiv:1811.03830, 2018 | 2 | 2018 |
| Interpretation of whole-slide images in digital pathology P Pati, G Jaume, AF Rodriguez, M Gabrani US Patent App. 16/953,377, 2022 | | 2022 |
| Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images K Thandiackal, B Chen, P Pati, G Jaume, DFK Williamson, M Gabrani, ... arXiv preprint arXiv:2204.12454, 2022 | | 2022 |
| Extracting structured information from a document containing filled form images AF Rodriguez, G Jaume, M Gabrani US Patent App. 17/531,912, 2022 | | 2022 |
| Graph Representation Learning and Explainability in Breast Cancer Pathology: Bridging the Gap between AI and Pathology Practice P Pati, G Jaume, A Foncubierta-Rodriguez, F Feroce, G Scognamiglio, ... Artificial Intelligence Applications In Human Pathology, 243, 2022 | | 2022 |
| Graph Representation Learning in Computational Pathology G Jaume EPFL, 2022 | | 2022 |
| Extracting structured information from a document containing filled form images AF Rodriguez, G Jaume, M Gabrani US Patent 11,188,713, 2021 | | 2021 |
| Extracting structured information from a document containing filled form images AF Rodriguez, G Jaume, M Gabrani US Patent 11,120,209, 2021 | | 2021 |
