Prashnna Kumar Gyawali

Artificial Intelligence · 2015

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Prashnna Kumar Gyawali trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Abdel-rahman Mohamed

Who trusts Prashnna Kumar Gyawali overall

  1. Alexander Rainer Tassilo Gepperth
  2. Benedikt Pfülb

Papers from Prashnna Kumar Gyawali's perspective

Ordered by how strongly the researchers Prashnna Kumar Gyawali trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Dropout: a simple way to prevent neural networks from overfitting
  4. Rectified Linear Units Improve Restricted Boltzmann Machines
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Long Short-Term Memory
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Why Does Unsupervised Pre-training Help Deep Learning?
  10. Learning Multiple Layers of Features from Tiny Images

Their papers