Sébastien Da Veiga

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Statistical Learning Theory — 15 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Statistics and Probability — 10 citations into it
• Algorithms & Complexity — 7 citations into it
• Computational Theory and Mathematics — 5 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Molecular Biology — 5 citations into it

Whom Sébastien Da Veiga trusts overall

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

1. Leo Breiman
2. Bin Yu
3. J. Ross Quinlan
4. Jerome H. Friedman
5. R. Rivest
6. Marjolein Fokkema
7. Robert Tibshirani
8. Trevor J. Hastie
9. Niko Speybroeck
10. Peter Clark

Who trusts Sébastien Da Veiga overall

1. Emilio Carrizosa

Papers from Sébastien Da Veiga's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. Bagging Predictors
3. Random Forests
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Long Short-Term Memory
7. ImageNet classification with deep convolutional neural networks
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Interpretable Random Forests via Rule Extraction (2020) — 77 citations
• Basics and Trends in Sensitivity Analysis (2021) — 113 citations
• SIRUS: making random forests interpretable (2019) — 10 citations