Francesco Donnarumma

Model Architectures · 2020

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Model Architectures — 25 citations into it
• Artificial Intelligence — 23 citations into it
• Computer Vision and Pattern Recognition — 23 citations into it
• Optimization & Training — 5 citations into it

Whom Francesco Donnarumma trusts overall

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

1. Yoshua Bengio
2. Yann LeCun
3. Geoffrey E. Hinton
4. Christian Szegedy
5. Sergey Ioffe
6. Kaiming He
7. Bernard Widrow
8. Alex Krizhevsky
9. Andrew L. Maas
10. Simon S. Haykin

Papers from Francesco Donnarumma's perspective

Ordered by how strongly the researchers Francesco Donnarumma 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• A survey on modern trainable activation functions (2020) — 533 citations