Céline Hudelot
Computer Vision and Pattern Recognition · 2008–2020
A researcher in the Science corpus: 6 papers; trusts 1,129 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 203 citations into it; #5,978 of 21,575 by trust here, #7,499 by citations
- Artificial Intelligence — 184 citations into it; #11,271 of 35,345 by trust here, #15,004 by citations
- Representation & Self-Supervised Learning — 105 citations into it; #2,048 of 3,145 by trust here, #2,454 by citations
- Generative Models — 45 citations into it
- Evaluation & Benchmarks — 24 citations into it
- Natural Language Processing — 22 citations into it
- Optimization & Training — 22 citations into it
- Graph Learning — 21 citations into it
Whom Céline Hudelot trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Diederik P. Kingma
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Ross B. Girshick
- Karen Simonyan
- Radford M. Neal
Who trusts Céline Hudelot overall
- Ivan Donadello
- Jamal Atif
- Lihe Yang
- Luciano Serafini
- Xiangli Yang
- Chong Zhou
- Rushi Jiao
- Xiangde Luo
- Eden Belouadah
- Yanbei Chen
Papers from Céline Hudelot's perspective
Ordered by how strongly the researchers Céline Hudelot trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Controlling generative models with continuous factors of variations (2020) — 133 citations
- Semi-Supervised Semantic Segmentation With Cross-Consistency Training (2020) — 964 citations
- An Overview of Deep Semi-Supervised Learning (2020) — 362 citations
- Fuzzy spatial relation ontology for image interpretation (2008) — 267 citations
- Learning More Universal Representations for Transfer-Learning (2017) — 60 citations
- Explanatory Reasoning for Image Understanding Using Formal Concept Analysis and Description Logics (2014) — 45 citations