Jan Ruben Zilke

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

Whom Jan Ruben Zilke trusts overall

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

  1. Hiroshi Tsukimoto
  2. Mark W. Craven
  3. Gethsiyal Augasta M
  4. Robert Andrews
  5. Kamal K. Sethi
  6. Gregor P. J. Schmitz
  7. José Manuel Benítez
  8. Thangairulappan Kathirvalavakumar
  9. Joachim Diederich
  10. Durgesh Kumar Mishra

Who trusts Jan Ruben Zilke overall

  1. Leilani H. Gilpin
  2. Gesina Schwalbe
  3. Mark T. Keane
  4. Nadia Burkart
  5. Vaishak Belle
  6. Vanessa Buhrmester
  7. Gabrielle Ras
  8. Qiang Huang
  9. David Bau
  10. Bettina Finzel

Papers from Jan Ruben Zilke's perspective

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

  1. Survey and critique of techniques for extracting rules from trained artificial neural networks
  2. Using Sampling and Queries to Extract Rules from Trained Neural Networks
  3. Gradient-based learning applied to document recognition
  4. Extracting Tree-Structured Representations of Trained Networks
  5. Reverse Engineering the Neural Networks for Rule Extraction in Classification Problems
  6. KDRuleEx: A Novel Approach for Enhancing User Comprehensibility Using Rule Extraction
  7. ANN-DT: an algorithm for extraction of decision trees from artificial neural networks
  8. Rule extraction from neural networks via decision tree induction
  9. Extracting rules from trained neural networks
  10. Are artificial neural networks black boxes?

Their papers