Sequence Modeling

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 134 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

Whom Sequence Modeling trusts overall

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

  1. Ilya Sutskever
  2. Alex Krizhevsky
  3. Alex Graves
  4. Geoffrey E. Hinton
  5. Yoshua Bengio
  6. Diederik P. Kingma
  7. Yann LeCun
  8. Oriol Vinyals
  9. Kaiming He
  10. Quoc V. Le

Who trusts Sequence Modeling overall

  1. Albert Gu
  2. Shaojie Bai
  3. Zachary Teed
  4. Guohao Li
  5. Vladlen Koltun
  6. Avi Schwarzschild
  7. Minhao Liu
  8. Karan Goel
  9. Jia Deng
  10. J. Kolter

Papers from Sequence Modeling's perspective

Ordered by how strongly the researchers Sequence Modeling 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. Long Short-Term Memory
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers