Emanuele Rossi

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 54 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 118 citations into it
• Graph Learning — 67 citations into it
• Statistical and Nonlinear Physics — 49 citations into it
• Computer Vision and Pattern Recognition — 48 citations into it
• Model Architectures — 23 citations into it
• Molecular Biology — 17 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Information Systems — 15 citations into it

Whom Emanuele Rossi trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yann LeCun
4. Yoshua Bengio
5. Kaiming He
6. Alex Krizhevsky
7. William L. Hamilton
8. Christian Szegedy
9. Jure Leskovec
10. Thomas Kipf

Who trusts Emanuele Rossi overall

1. Michelle M. Li
2. Joakim Skarding
3. Guohao Li
4. Qian Huang
5. Weihua Hu
6. Kexin Huang
7. Bogdan Gabrys

Papers from Emanuele Rossi's perspective

Ordered by how strongly the researchers Emanuele Rossi 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• SIGN: Scalable Inception Graph Neural Networks (2020) — 475 citations
• GRAND: Graph Neural Diffusion (2021) — 391 citations
• Temporal Graph Networks for Deep Learning on Dynamic Graphs (2020) — 1,099 citations