Gary Bécigneul

Artificial Intelligence · 2018

A researcher in the Science corpus: 4 papers; trusts 79 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it; #6,833 of 35,345 by trust here, #17,776 by citations
• Natural Language Processing — 23 citations into it
• Representation & Self-Supervised Learning — 20 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it; #7,627 of 21,575 by trust here, #18,782 by citations
• Computational Theory and Mathematics — 9 citations into it; #7,085 of 12,182 by trust here, #7,142 by citations
• Statistical and Nonlinear Physics — 8 citations into it
• Management Science and Operations Research — 6 citations into it
• Numerical Analysis — 6 citations into it

Whom Gary Bécigneul trusts overall

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

1. Maximilian Nickel
2. Silvere Bonnabel
3. Diederik P. Kingma
4. Octavian-Eugen Ganea
5. Matthew D. Zeiler
6. John C. Duchi
7. Geoffrey E. Hinton
8. Tomas Mikolov
9. Douwe Kiela
10. Yoshua Bengio

Who trusts Gary Bécigneul overall

1. Ivana Balazevic
2. A. Tifrea
3. Ines Chami
4. Mario Lezcano Casado
5. Valentin Khrulkov
6. Qi Liu
7. Jun Li
8. Octavian-Eugen Ganea
9. Carl Allen
10. Sidak Pal Singh

Papers from Gary Bécigneul's perspective

Ordered by how strongly the researchers Gary Bécigneul 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Riemannian Adaptive Optimization Methods (2018) — 355 citations
• Hyperbolic Neural Networks (2018) — 842 citations
• Poincaré GloVe: Hyperbolic Word Embeddings (2018) — 343 citations
• Hyperbolic Entailment Cones for Learning Hierarchical Embeddings (2018) — 360 citations