Akshay Chandrashekaran

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 69 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Akshay Chandrashekaran trusts overall

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

  1. Kaiming He
  2. Alex Krizhevsky
  3. Katharina Eggensperger
  4. Yoshua Bengio
  5. Daniel Povey
  6. Jasper Snoek
  7. Geoffrey E. Hinton
  8. James Bergstra
  9. Andreas Stolcke
  10. X. Zhang

Who trusts Akshay Chandrashekaran overall

  1. Martin Wistuba
  2. Pengzhen Ren
  3. Ambrish Rawat
  4. Tejaswini Pedapati
  5. Kazuki Irie
  6. Qiantong Xu
  7. Abdel-rahman Mohamed
  8. Tatiana Likhomanenko
  9. Yun Xiao
  10. Awni Y. Hannun

Papers from Akshay Chandrashekaran's perspective

Ordered by how strongly the researchers Akshay Chandrashekaran 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. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  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