S. Stodtmann

Artificial Intelligence · 2024

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

• Artificial Intelligence — 7 citations into it

Whom S. Stodtmann trusts

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

1. Scott M. Lundberg (in Artificial Intelligence)
2. Su-In Lee (in Artificial Intelligence)
3. Igor Kononenko (in Artificial Intelligence)

Papers from S. Stodtmann's perspective

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

1. An Efficient Explanation of Individual Classifications using Game Theory
2. A Unified Approach to Interpreting Model Predictions
3. From Local Explanations to Global Understanding with Explainable AI for Trees
4. A Value for n-person Games
5. Polynomial calculation of the Shapley value based on sampling (Computers & Operations Research)
6. Explaining Classifications For Individual Instances
7. Anchors: High-Precision Model-Agnostic Explanations
8. Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
9. Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
10. Striving for Simplicity: The All Convolutional Net

Their papers

• Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development (2024) — 634 citations