Siamak Ravanbakhsh

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 9 papers; trusts 305 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

Whom Siamak Ravanbakhsh trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Max Welling
  4. Taco Cohen
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Yann LeCun
  8. Jimmy Ba
  9. Kaiming He
  10. Ilya Sutskever

Who trusts Siamak Ravanbakhsh overall

  1. David W. Romero
  2. Haggai Maron
  3. Taco Cohen
  4. Jean-Baptiste Cordonnier
  5. Benjamin Bloem-Reddy
  6. Jonathan Gordon
  7. Nimrod Segol
  8. Hadar Serviansky
  9. Max Horn
  10. Han-Jia Ye

Papers from Siamak Ravanbakhsh's perspective

Ordered by how strongly the researchers Siamak Ravanbakhsh 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. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  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. Learning Multiple Layers of Features from Tiny Images
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers