Gagandeep Singh

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Gagandeep Singh trusts overall

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

  1. Alex Krizhevsky
  2. Rüdiger Ehlers
  3. Matthew Mirman
  4. Ian J. Goodfellow
  5. Nicholas Carlini
  6. Vincent Tjeng
  7. Yann LeCun
  8. Timon Gehr
  9. Guy Katz
  10. Geoffrey E. Hinton

Who trusts Gagandeep Singh overall

  1. Huan Zhang
  2. Hadi Salman
  3. Timon Gehr
  4. Matt Jordan
  5. Shiqi Wang
  6. Kaidi Xu
  7. Pawel Morawiecki
  8. Greg Yang
  9. Bernd Finkbeiner
  10. Petar Tsankov

Papers from Gagandeep Singh's perspective

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

Their papers