Leonardo Petrini

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Scaling & Learning Theory — 11 citations into it
• Statistical and Nonlinear Physics — 8 citations into it
• Model Architectures — 5 citations into it

Whom Leonardo Petrini trusts overall

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

1. E. Gardner
2. Madhu S. Advani
3. Arthur Jacot
4. R. Dietrich
5. Andrew M. Saxe
6. Mingxing Tan

Who trusts Leonardo Petrini overall

1. Mario Geiger

Papers from Leonardo Petrini's perspective

Ordered by how strongly the researchers Leonardo Petrini 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Neural Tangent Kernel: Convergence and Generalization in Neural Networks
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Geometric compression of invariant manifolds in neural nets (2020) — 14 citations