Paolo Rota

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 233 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 106 citations into it
• Computer Vision and Pattern Recognition — 103 citations into it
• Meta & Continual Learning — 19 citations into it
• Model Architectures — 19 citations into it
• Optimization & Training — 14 citations into it

Whom Paolo Rota trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Ilya Sutskever
7. Yann LeCun
8. Ross B. Girshick
9. Alex Graves
10. Karen Simonyan

Papers from Paolo Rota's perspective

Ordered by how strongly the researchers Paolo Rota 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation (2022) — 97 citations
• Curriculum Learning: A Survey (2021) — 577 citations
• Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound (2020) — 462 citations