D. Richard Kuhn
Artificial Intelligence · 2007–2020
A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 10 citations into it
- Safety, Robustness & Interpretability — 8 citations into it
Whom D. Richard Kuhn trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from D. Richard Kuhn's perspective
Ordered by how strongly the researchers D. Richard Kuhn trusts endorse each paper. Same corpus, a different order for every researcher.
- Explanation in Artificial Intelligence: Insights from the Social Sciences
- Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences
- The course of events: counterfactuals, causal sequences, and explanation
- Explanation and Justification in Machine Learning : A Survey Or
- A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI
- Explainable artificial intelligence: A survey
- Explainable Recommendation: A Survey and New Perspectives
- What do we need to build explainable AI systems for the medical domain?
- Contrastive Explanation
- An investigation of the applicability of design of experiments to software testing (27th Annual NASA Goddard/IEEE Software Engineering Workshop, 2002. Proceedings.)
Their papers
- Combinatorial Methods for Explainable AI (2020) — 26 citations
- IPOG: A General Strategy for T-Way Software Testing (2007) — 386 citations