Matthew Jörke

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Matthew Jörke trusts overall

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

  1. John K. Kruschke
  2. Matthew Botvinick
  3. Wouter Kool
  4. Peter Hase

Papers from Matthew Jörke's perspective

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

  1. Explanation in Artificial Intelligence: Insights from the Social Sciences
  2. A Unified Approach to Interpreting Model Predictions
  3. Manipulating and Measuring Model Interpretability
  4. SQuAD: 100,000+ Questions for Machine Comprehension of Text
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Too much, too little, or just right? Ways explanations impact end users' mental models
  7. How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation
  8. Trust in Automation: Designing for Appropriate Reliance
  9. Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?
  10. The structure and function of explanations.

Their papers