Mauro Castelli

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 3 papers; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Mauro Castelli trusts overall

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

  1. Alex Krizhevsky
  2. Karen Simonyan
  3. Dominic Masters
  4. Yoshua Bengio
  5. Geoffrey E. Hinton
  6. Ilya Sutskever
  7. Andrew Zisserman
  8. Yann LeCun
  9. Kaiming He
  10. Sergey Ioffe

Papers from Mauro Castelli's perspective

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

Their papers