Lukas Mauch

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Lukas Mauch trusts overall

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

  1. Alex Krizhevsky
  2. Radford M. Neal
  3. Dimitri P. Bertsekas
  4. Yoshua Bengio
  5. Kaiming He
  6. Geoffrey E. Hinton
  7. Jia Deng
  8. Diederik P. Kingma
  9. X. Zhang

Who trusts Lukas Mauch overall

  1. Markus Nagel

Papers from Lukas Mauch's perspective

Ordered by how strongly the researchers Lukas Mauch 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. ImageNet: A large-scale hierarchical image database
  4. Learning Multiple Layers of Features from Tiny Images
  5. Gradient-based learning applied to document recognition
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  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. Going deeper with convolutions

Their papers