Pierre-Alain Muller

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 50 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Pierre-Alain Muller trusts overall

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

  1. Yoshua Bengio
  2. Yann LeCun
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Kaiming He
  6. Alex Krizhevsky
  7. Radford M. Neal
  8. Ilya Sutskever
  9. Christian Szegedy
  10. Anthony J. Bagnall

Who trusts Pierre-Alain Muller overall

  1. Angus Dempster

Papers from Pierre-Alain Muller's perspective

Ordered by how strongly the researchers Pierre-Alain Muller 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Going deeper with convolutions
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. ImageNet: A large-scale hierarchical image database
  10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers