Florian Yger
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 62 citations into it
- Cognitive Neuroscience — 52 citations into it; #5,579 of 10,852 by trust here, #6,360 by citations
- Computer Vision and Pattern Recognition — 36 citations into it
- Safety, Robustness & Interpretability — 29 citations into it
- Signal Processing — 21 citations into it
- Cellular and Molecular Neuroscience — 18 citations into it; #1,464 of 2,998 by trust here, #2,766 by citations
- Electrical and Electronic Engineering — 15 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
Whom Florian Yger trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Fabien Lotte
- Alexandre Barachant
- Benjamin Blankertz
- Corinna Cortes
- K. Müller
- Vincent Arsigny
- Stéphane Bonnet
- Muhammad Naeem
- Alex Krizhevsky
- Marco Congedo
Who trusts Florian Yger overall
Papers from Florian Yger's perspective
Ordered by how strongly the researchers Florian Yger 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
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document 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
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family (2019) — 91 citations
- A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update (2018) — 2,013 citations
- Riemannian Approaches in Brain-Computer Interfaces: A Review (2017) — 390 citations