Neta Shaul

Computer Vision and Pattern Recognition · 2023–2024

A researcher in the Science corpus: 3 papers; trusts 33 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Neta Shaul trusts overall

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

  1. Jonathan Ho
  2. Diederik P. Kingma
  3. Alex Krizhevsky
  4. Geoffrey E. Hinton
  5. Yoshua Bengio
  6. Yang Song
  7. Jascha Narain Sohl-Dickstein
  8. Lawrence F. Shampine
  9. Kaiming He
  10. Jia Deng

Who trusts Neta Shaul overall

  1. Apoorv Vyas

Papers from Neta Shaul's perspective

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

Their papers