Giovanni Zappella

Artificial Intelligence · 2013–2022

A researcher in the Science corpus: 5 papers; trusts 330 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 145 citations into it; #19,271 of 35,345 by trust here, #26,682 by citations
• Computer Vision and Pattern Recognition — 99 citations into it; #14,491 of 21,575 by trust here, #20,271 by citations
• Meta & Continual Learning — 63 citations into it
• Representation & Self-Supervised Learning — 36 citations into it
• Natural Language Processing — 29 citations into it
• Model Architectures — 24 citations into it
• Reinforcement Learning — 17 citations into it
• Radiology, Nuclear Medicine and Imaging — 14 citations into it

Whom Giovanni Zappella trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Kaiming He
6. Yann LeCun
7. Ilya Sutskever
8. Marc'Aurelio Ranzato
9. Ross B. Girshick
10. Radford M. Neal

Who trusts Giovanni Zappella overall

1. B. Ermiş
2. Qingyun Wu
3. Kamyar Azizzadenesheli
4. Hongning Wang
5. Yanzhe Zhang
6. Liyuan Wang

Papers from Giovanni Zappella's perspective

Ordered by how strongly the researchers Giovanni Zappella 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Online Clustering of Bandits (2014) — 289 citations
• Memory Efficient Continual Learning with Transformers (2022) — 70 citations
• Continual Learning with Transformers for Image Classification (2022) — 27 citations
• Memory Efficient Continual Learning for Neural Text Classification (2022) — 5 citations
• A Gang of Bandits (2013) — 174 citations