Jörn-Philipp Lies

Cognitive Neuroscience · 2014

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Jörn-Philipp Lies trusts overall

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

  1. Aapo Hyvärinen
  2. William T. Freeman
  3. Nicole C. Rust
  4. Christoph Kayser
  5. Pietro Berkes
  6. Laurenz Wiskott
  7. Patrik O. Hoyer
  8. Edward H. Adelson
  9. Odelia Schwartz
  10. Wolfgang Einhäuser

Who trusts Jörn-Philipp Lies overall

  1. Dinesh Jayaraman
  2. Kristen Grauman
  3. Ross Goroshin
  4. Joan Bruna

Papers from Jörn-Philipp Lies's perspective

Ordered by how strongly the researchers Jörn-Philipp Lies trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Slow Feature Analysis: Unsupervised Learning of Invariances
  2. Gradient-based learning applied to document recognition
  3. Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces
  4. ImageNet classification with deep convolutional neural networks
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Slow feature analysis yields a rich repertoire of complex cell properties.
  8. Spatiotemporal elements of macaque v1 receptive fields.
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. ImageNet: A large-scale hierarchical image database

Their papers