Francesco Rinaldi

Optimization & Training · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Francesco Rinaldi trusts overall

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

  1. Simon Lacoste-Julien
  2. Jérôme Bolte
  3. Zhi-Quan Tom Luo
  4. Hédy Attouch
  5. Martin Jaggi
  6. Philip Wolfe
  7. Paul Tseng
  8. Gábor Braun
  9. Aris Daniilidis
  10. Yurii E. Nesterov

Who trusts Francesco Rinaldi overall

  1. Thomas Kerdreux

Papers from Francesco Rinaldi's perspective

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

Their papers