Sheikh Khaled Ghafoor

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Safety, Robustness & Interpretability — 8 citations into it
• Accounting — 5 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Finance — 5 citations into it

Whom Sheikh Khaled Ghafoor trusts

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

1. Igor Kononenko (in Artificial Intelligence)
2. Erik Strumbelj (in Artificial Intelligence)
3. Scott M. Lundberg (in Artificial Intelligence)
4. Su-In Lee (in Artificial Intelligence)
5. Rakesh Agrawal (in Algorithms & Complexity)
6. Rayadurgam Srikant (in Algorithms & Complexity)
7. Stan Lipovetsky (in Computer Vision and Pattern Recognition)
8. Marianna Kudlyak (in Accounting)

Papers from Sheikh Khaled Ghafoor's perspective

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

1. Random Forests
2. Scikit-learn: Machine Learning in Python
3. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
4. On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
5. The mythos of model interpretability
6. Learning Important Features Through Propagating Activation Differences
7. Greedy function approximation: A gradient boosting machine.
8. A Unified Approach to Interpreting Model Predictions
9. A training algorithm for optimal margin classifiers
10. Explanation in Artificial Intelligence: Insights from the Social Sciences

Their papers

• Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction (2019) — 25 citations