Rahul

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Rahul trusts overall

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

  1. Stanley J. Osher
  2. Diederik P. Kingma
  3. Mengyu Chu
  4. Makoto Matsumoto
  5. Michaël Defferrard
  6. Jan S. Hesthaven
  7. Cheng Yang
  8. Jonathan Tompson
  9. Jimmy Ba
  10. Geoffrey E. Hinton

Papers from Rahul's perspective

Ordered by how strongly the researchers Rahul 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. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Gradient-based learning applied to document recognition
  5. Dropout: a simple way to prevent neural networks from overfitting
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Learning Multiple Layers of Features from Tiny Images
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet: A large-scale hierarchical image database

Their papers