Ankur Agrawal

Computer Vision and Pattern Recognition · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 47 researchers and is trusted by 59 researchers here, as inferred from the citation graph.

Subfields

Whom Ankur Agrawal trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Yann LeCun
  4. Yoshua Bengio
  5. Ilya Sutskever
  6. Diederik P. Kingma
  7. Kaiming He
  8. L. Eon Bottou
  9. Ruslan Salakhutdinov
  10. Simon S. Haykin

Who trusts Ankur Agrawal overall

  1. Markus Nagel
  2. Mohammad Mohammadi Amiri
  3. Ahmed Khaled
  4. Tim Dettmers
  5. Georgios Georgiadis
  6. Yunhui Guo
  7. Yu Cheng
  8. Jia-Nan Wu
  9. Deniz Gündüz
  10. Yu-hsin Chen

Papers from Ankur Agrawal's perspective

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

Their papers