Joel Vaughan

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it

Whom Joel Vaughan trusts overall

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

1. Simon N. Wood
2. Deborah Silver
3. Ilya M. Sobol
4. Leonardo S. Bastos
5. Minsuk Kahng
6. Anthony OʼHagan
7. Sergei S. Kucherenko
8. Runze Li
9. Pierre Yves Andrews
10. Agus Sudjianto

Papers from Joel Vaughan's perspective

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

1. Distilling the Knowledge in a Neural Network (arXiv.org)
2. Axiomatic Attribution for Deep Networks
3. Model compression
4. Projection Pursuit Regression
5. Towards better understanding of gradient-based attribution methods for Deep Neural Networks
6. Transparent Model Distillation
7. Diagnostics for Gaussian Process Emulators (Technometrics)
8. Design and Modeling for Computer Experiments
9. Feature Visualization
10. ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models

Their papers

• Explainable Neural Networks based on Additive Index Models (2018) — 112 citations