Jakob Wasserthal

Computer Vision and Pattern Recognition · 2018–2022

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Jakob Wasserthal trusts overall

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

  1. Diederik P. Kingma
  2. Vinod Nair
  3. Geoffrey E. Hinton
  4. Olaf Ronneberger
  5. Brian B. Avants
  6. Jimmy Ba
  7. Ben Jeurissen
  8. David C. Van Essen
  9. Jacques-Donald Tournier
  10. Philipp Fischer

Who trusts Jakob Wasserthal overall

  1. Arvid Lundervold
  2. Fabian Isensee

Papers from Jakob Wasserthal's perspective

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

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

Their papers