Sharon Gannot

Signal Processing · 2001–2020

A researcher in the Science corpus: 9 papers; trusts 62 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

Whom Sharon Gannot trusts overall

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

  1. P. Loizou
  2. Lucas C. Parra
  3. Simon Doclo
  4. Nobutaka Ono
  5. Özgür Yilmaz
  6. Hiroshi Sawada
  7. Jean-François Cardoso
  8. Deliang Wang
  9. Emmanuel Vincent
  10. Radford M. Neal

Who trusts Sharon Gannot overall

  1. Bracha Laufer-Goldshtein
  2. Eliya Nachmani
  3. Mehrez Souden
  4. Shmulik Markovich Golan
  5. Sanyuan Chen
  6. Zhong-Qiu Wang
  7. Matthew Maciejewski
  8. Soumitro Chakrabarty
  9. Jonathan Le Roux
  10. Kateřina Žmolíková

Papers from Sharon Gannot's perspective

Ordered by how strongly the researchers Sharon Gannot trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Dropout: a simple way to prevent neural networks from overfitting
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers