V. Nair

Artificial Intelligence · with Sudjianto · 2018

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom V. Nair trusts overall

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

  1. Jerome H. Friedman
  2. Daniel W. Apley
  3. Marco Tulio Ribeiro
  4. Sarah Tan
  5. Leonardo S. Bastos
  6. A. Goldstein
  7. Simon N. Wood
  8. Deborah Silver
  9. Ilya M. Sobol
  10. R. Caruana

Who trusts V. Nair overall

  1. Christoph Molnar
  2. Lev V. Utkin

Papers from V. Nair's perspective

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

  1. Distilling the Knowledge in a Neural Network (arXiv.org)
  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. Axiomatic Attribution for Deep Networks
  5. Towards better understanding of gradient-based attribution methods for Deep Neural Networks
  6. Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation
  7. Transparent Model Distillation
  8. ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
  9. Design and Modeling for Computer Experiments
  10. Projection Pursuit Regression

Their papers