Peter Maass

Computer Vision and Pattern Recognition · 2006–2019

A researcher in the Science corpus: 9 papers; trusts 220 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Peter Maass trusts overall

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

  1. Ingrid Daubechies
  2. Stéphane Mallat
  3. Yann LeCun
  4. Geoffrey E. Hinton
  5. Diederik P. Kingma
  6. Kaiming He
  7. Alex Krizhevsky
  8. Yoshua Bengio
  9. David L. Donoho
  10. Bernd Hofmann

Who trusts Peter Maass overall

  1. Bangti Jin
  2. Simon Robert Arridge

Papers from Peter Maass's perspective

Ordered by how strongly the researchers Peter Maass 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  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