Guillaume Jaume
Artificial Intelligence · 2019–2024
A researcher in the Science corpus: 4 papers; trusts 9 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 128 citations into it
- Computer Vision and Pattern Recognition — 54 citations into it; #18,189 of 21,575 by trust here, #15,162 by citations
- Model Architectures — 7 citations into it
- Natural Language Processing — 6 citations into it
Whom Guillaume Jaume trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Raymond W. Smith
- Kaiming He
- Jacob Devlin
- Adam W. Harley
- X. Zhang
- Shaoqing Ren
- Geoffrey E. Hinton
- Ming Y. Lu
- Alex Krizhevsky
- Yann LeCun
Who trusts Guillaume Jaume overall
Papers from Guillaume Jaume's perspective
Ordered by how strongly the researchers Guillaume Jaume trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- A visual-language foundation model for computational pathology (2024) — 1,028 citations
- Towards a General-Purpose Foundation Model for Computational Pathology (2024) — 1,590 citations
- Artificial intelligence for digital and computational pathology (2023) — 348 citations
- FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents (2019) — 510 citations