Guillaume Jaume

Orcid: 0000-0002-3832-1390

According to our database1, Guillaume Jaume authored at least 21 papers between 2017 and 2024.

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Bibliography

2024
Artificial Intelligence for Digital and Computational Pathology.
CoRR, 2024

2023
Weakly supervised joint whole-slide segmentation and classification in prostate cancer.
Medical Image Anal., October, 2023

A General-Purpose Self-Supervised Model for Computational Pathology.
CoRR, 2023

Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples.
CoRR, 2023

Towards a Visual-Language Foundation Model for Computational Pathology.
CoRR, 2023

Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction.
CoRR, 2023

Embedding Space Augmentation for Weakly Supervised Learning in Whole-Slide Images.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022
Hierarchical graph representations in digital pathology.
Medical Image Anal., 2022

BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images.
Database J. Biol. Databases Curation, 2022

Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Hierarchical Cell-to-Tissue Graph Representations for Breast Cancer Subtyping in Digital Pathology.
CoRR, 2021

Learning Whole-Slide Segmentation from Inexact and Incomplete Labels Using Tissue Graphs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Quantifying Explainers of Graph Neural Networks in Computational Pathology.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

HistoCartography: A Toolkit for Graph Analytics in Digital Pathology.
Proceedings of the MICCAI Workshop on Computational Pathology, 2021

Histocartography: a pipeline for histology image analysis.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020
Towards Explainable Graph Representations in Digital Pathology.
CoRR, 2020

HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 2020

2019
edGNN: a Simple and Powerful GNN for Directed Labeled Graphs.
CoRR, 2019

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents.
Proceedings of the 2nd International Workshop on Open Services and Tools for Document Analysis, 2019

2018
Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks.
CoRR, 2018

2017
Interpreting Data from Scanned Tables.
Proceedings of the 12th International Workshop on Graphics Recognitio, 2017


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