Gilles Wainrib

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it
• Cognitive Neuroscience — 16 citations into it
• Signal Processing — 10 citations into it
• Optimization & Training — 9 citations into it

Whom Gilles Wainrib trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Tianqi Chen
3. Jerome H. Friedman
4. Yann LeCun
5. Geoffrey E. Hinton
6. Greg Ridgeway
7. Jimmy Ba
8. Yoshua Bengio
9. Orestis Tsinalis

Papers from Gilles Wainrib's perspective

Ordered by how strongly the researchers Gilles Wainrib trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Dropout: a simple way to prevent neural networks from overfitting
6. Gradient-based learning applied to document recognition
7. Learning Multiple Layers of Features from Tiny Images
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. ImageNet: A large-scale hierarchical image database

Their papers

• ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors (2018) — 26 citations
• A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series (2017) — 565 citations
• A deep learning model to predict RNA-Seq expression of tumours from whole slide images (2020) — 475 citations
• Deep learning-based classification of mesothelioma improves prediction of patient outcome (2019) — 488 citations