G. Eds

Model Architectures · 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 G. Eds 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

Papers from G. Eds's perspective

Ordered by how strongly the researchers G. Eds 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. Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks
  8. Supervised neural networks for the classification of structures
  9. The Recurrent Cascade-Correlation Architecture
  10. Learning Complex, Extended Sequences Using the Principle of History Compression

Their papers