Pedro Tabacof

Artificial Intelligence · 2015–2016

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

Whom Pedro Tabacof trusts overall

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

  1. Ian J. Goodfellow
  2. Yann LeCun
  3. Christian Szegedy
  4. Yoshua Bengio
  5. Geoffrey E. Hinton
  6. Diederik P. Kingma
  7. Alex Krizhevsky
  8. Ilya Sutskever
  9. Jonathon Shlens
  10. Karol Gregor

Who trusts Pedro Tabacof overall

  1. Jake Zhao
  2. A. Serban
  3. Katja Auernhammer
  4. Naveed Akhtar
  5. Sara Sabour
  6. Xiaoyong Yuan
  7. Jernej Kos
  8. Alhussein Fawzi
  9. Pierre Stock
  10. Laurent Amsaleg

Papers from Pedro Tabacof's perspective

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

Their papers