R. Lee

Model Architectures · with Eds · 2001

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom R. Lee trusts overall

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

  1. Scott E. Fahlman
  2. Alessandro Sperduti
  3. Ronald J. Williams
  4. G. Puskorius
  5. Paolo Frasconi
  6. J. Urgen Schmidhuber
  7. Eduardo Sontag
  8. David Zipser

Papers from R. Lee's perspective

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

  1. Long Short-Term Memory
  2. Learning long-term dependencies with gradient descent is difficult
  3. A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
  4. A general framework for adaptive processing of data structures
  5. Learning long-term dependencies in NARX recurrent neural networks
  6. Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network
  7. Gradient-based learning applied to document recognition
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks
  10. Supervised neural networks for the classification of structures

Their papers