Enrico Bagli

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Statistics and Probability — 12 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Enrico Bagli trusts overall

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

1. Jerome H. Friedman
2. Marco Tulio Ribeiro
3. Alan Agresti
4. Davide Chicco
5. Trevor J. Hastie
6. Bradley C. Boehmke
7. Yichen Zhou
8. Daniel W. Apley
9. William H. Greene
10. Sameer Singh

Papers from Enrico Bagli's perspective

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

1. Random Forests
2. Greedy function approximation: A gradient boosting machine.
3. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
4. Anchors: High-Precision Model-Agnostic Explanations
5. A Unified Approach to Interpreting Model Predictions
6. Ridge Regression: Biased Estimation for Nonorthogonal Problems
7. The Balanced Accuracy and Its Posterior Distribution (International Conference on Pattern Recognition)
8. Comparison of the predicted and observed secondary structure of T4 phage lysozyme.
9. Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
10. A Survey of Methods for Explaining Black Box Models

Their papers

• Metrics for Multi-Class Classification: an Overview (2020) — 1,297 citations
• Statistical stability indices for LIME: Obtaining reliable explanations for machine learning models (2020) — 219 citations