Claudio Baecchi

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 206 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 67 citations into it
• Artificial Intelligence — 59 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Model Architectures — 18 citations into it
• Signal Processing — 8 citations into it

Whom Claudio Baecchi trusts overall

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

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

Who trusts Claudio Baecchi overall

1. Da-Wei Zhou

Papers from Claudio Baecchi's perspective

Ordered by how strongly the researchers Claudio Baecchi 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Learning Multiple Layers of Features from Tiny Images
9. Long Short-Term Memory
10. Going deeper with convolutions

Their papers

• Regular Polytope Networks (2021) — 35 citations
• Class-incremental Learning with Pre-allocated Fixed Classifiers (2020) — 44 citations