Franz Scherr

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Franz Scherr trusts overall

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

  1. Ronald J. Williams
  2. Arild Nøkland
  3. Yoshua Bengio
  4. Wulfram Gerstner
  5. Alex Graves
  6. Geoffrey E. Hinton
  7. Friedemann Zenke
  8. David Sussillo
  9. Corentin Tallec
  10. Richard S. Sutton

Papers from Franz Scherr's perspective

Ordered by how strongly the researchers Franz Scherr 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  6. Reinforcement Learning: An Introduction
  7. Learning Multiple Layers of Features from Tiny Images
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet: A large-scale hierarchical image database
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers