Davide Eynard

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 5 papers; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 109 citations into it
• Graph Learning — 65 citations into it
• Computer Vision and Pattern Recognition — 47 citations into it
• Statistical and Nonlinear Physics — 47 citations into it
• Computational Mechanics — 23 citations into it
• Model Architectures — 19 citations into it
• Representation & Self-Supervised Learning — 19 citations into it
• Molecular Biology — 17 citations into it

Whom Davide Eynard trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Andrew Y. Ng
4. Diederik P. Kingma
5. Yoshua Bengio
6. Mikhail Belkin
7. Alex Krizhevsky
8. Kaiming He
9. Michael I. Jordan
10. Ilya Sutskever

Who trusts Davide Eynard overall

1. Michael M. Bronstein
2. Davide Boscaini
3. Joan Bruna

Papers from Davide Eynard's perspective

Ordered by how strongly the researchers Davide Eynard 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• SIGN: Scalable Inception Graph Neural Networks (2020) — 475 citations
• Multimodal Manifold Analysis by Simultaneous Diagonalization of Laplacians (2015) — 67 citations
• Fake News Detection on Social Media using Geometric Deep Learning (2019) — 566 citations
• Temporal Graph Networks for Deep Learning on Dynamic Graphs (2020) — 1,099 citations
• Shape‐from‐Operator: Recovering Shapes from Intrinsic Operators (2015) — 48 citations