Gabriele Graffieti

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it; #22,119 of 35,345 by trust here, #14,718 by citations
• Computer Vision and Pattern Recognition — 35 citations into it; #13,697 of 21,575 by trust here, #10,010 by citations
• Meta & Continual Learning — 23 citations into it; #711 of 1,041 by trust here, #529 by citations
• Representation & Self-Supervised Learning — 13 citations into it
• Optimization & Training — 7 citations into it

Whom Gabriele Graffieti trusts overall

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

1. Vincenzo Lomonaco
2. Sergey Ioffe
3. Davide Maltoni
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Georgios Georgiadis
7. Tyler L. Hayes
8. Yoshua Bengio
9. Zhizhong Li
10. Kaiming He

Who trusts Gabriele Graffieti overall

1. Vincenzo Lomonaco
2. German Ignacio Parisi
3. Yabin Wang
4. Magdalena Biesialska
5. Zhiwu Huang

Papers from Gabriele Graffieti's perspective

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

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

Their papers

• Avalanche: an End-to-End Library for Continual Learning (2021) — 219 citations
• Latent Replay for Real-Time Continual Learning (2019) — 193 citations