Joan Alexis Glaunès

Computer Vision and Pattern Recognition · 2005–2020

A researcher in the Science corpus: 4 papers; trusts 28 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 39 citations into it
• Artificial Intelligence — 25 citations into it
• Computational Mechanics — 16 citations into it; #3,802 of 10,001 by trust here, #7,501 by citations
• Model Architectures — 9 citations into it
• Optimization & Training — 9 citations into it; #1,650 of 2,601 by trust here, #2,081 by citations
• Statistics and Probability — 9 citations into it
• Applied Mathematics — 8 citations into it
• Computational Theory and Mathematics — 8 citations into it

Whom Joan Alexis Glaunès trusts overall

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

1. Grace Wahba
2. Michael I. Miller
3. Hubert Nguyen
4. I. J. Schoenberg
5. Laurent Schwartz
6. Sarang C. Joshi
7. Haili Chui
8. Marc Vaillant
9. Sergey Ioffe
10. Laurent Younes

Who trusts Joan Alexis Glaunès overall

1. Freyr Sverrisson
2. Jean Feydy
3. Mario Micheli
4. Bruno E. Correia
5. Simon L. Cotter
6. Sylvain Arguillère

Papers from Joan Alexis Glaunès's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Kernel Operations on the GPU, with Autodiff, without Memory Overflows (2020) — 222 citations
• Fast geometric learning with symbolic matrices (2020) — 49 citations
• Matrix-valued kernels for shape deformation analysis (2013) — 52 citations
• Surface Matching via Currents (2005) — 471 citations