Sid Bundy

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 Sid Bundy trusts overall

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

1. Erik Strumbelj
2. Stan Lipovetsky
3. Scott M. Lundberg
4. Rakesh Agrawal

Papers from Sid Bundy's perspective

Ordered by how strongly the researchers Sid Bundy 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. Greedy function approximation: A gradient boosting machine.
7. Learning Important Features Through Propagating Activation Differences
8. A training algorithm for optimal margin classifiers
9. A Unified Approach to Interpreting Model Predictions
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