Mikael Johansson

Optimization & Training · IEEE Transactions on Communications · 2003–2018

A researcher in the Science corpus: 11 papers; trusts 55 researchers and is trusted by 53 researchers here, as inferred from the citation graph.

Subfields

Whom Mikael Johansson trusts overall

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

  1. Yurii E. Nesterov
  2. Tamer Basar
  3. Dimitri P. Bertsekas
  4. Ryuichi Oka
  5. Alex Krizhevsky
  6. John N. Tsitsiklis
  7. David D. Lewis
  8. Kaiming He
  9. Boris Polyak
  10. Geoffrey E. Hinton

Who trusts Mikael Johansson overall

  1. Sigurður F. Marinósson
  2. Xuping Xu
  3. Sudip K. Mazumder
  4. Mattias Nordin
  5. Xiangru Lian
  6. Sebastian U. Stich
  7. Anastasia Koloskova
  8. Ali H. Sayed
  9. Angelia Nedić
  10. Nicolas Loizou

Papers from Mikael Johansson's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Learning Multiple Layers of Features from Tiny Images
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers