Neil Shah

Signal Processing · with Patil · 2018

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Neil Shah trusts overall

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

  1. P. Loizou
  2. Diederik P. Kingma
  3. Yuxuan Wang
  4. Santiago Pascual
  5. Cees H. Taal
  6. Deliang Wang
  7. Jimmy Ba
  8. Felix Weninger

Who trusts Neil Shah overall

  1. Szu-Wei Fu
  2. Dacheng Yin
  3. Adam Polyak
  4. Chengyu Zheng
  5. Hyeong-Seok Choi
  6. Mohammad Nikzad

Papers from Neil Shah's perspective

Ordered by how strongly the researchers Neil Shah 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. GENERATIVE ADVERSARIAL NETS
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Long Short-Term Memory
  5. ImageNet classification with deep convolutional neural networks
  6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  7. Gradient-based learning applied to document recognition
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers