Stéphane Cotin

Medical Image Anal. · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Stéphane Cotin trusts overall

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

1. Diederik P. Kingma

Papers from Stéphane Cotin's perspective

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

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

Their papers

• Simulation of hyperelastic materials in real-time using Deep Learning (2019) — 336 citations