Jay Budzik

Artificial Intelligence · 2000–2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Jay Budzik trusts overall

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

  1. Lloyd S. Shapley
  2. Scott M. Lundberg
  3. Gerard A. Salton

Who trusts Jay Budzik overall

  1. Matthias Baldauf
  2. Diane Kelly
  3. Steve Lawrence
  4. Schahram Dustdar
  5. Thomas G. Dietterich
  6. Ryen W. White
  7. Evgeniy Gabrilovich
  8. Florian Rosenberg
  9. Tongshuang Sherry Wu
  10. Lynda Tamine

Papers from Jay Budzik's perspective

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

  1. Axiomatic Attribution for Deep Networks
  2. Scikit-learn: Machine Learning in Python
  3. A Unified Approach to Interpreting Model Predictions
  4. Consistent Individualized Feature Attribution for Tree Ensembles
  5. A Value for n-person Games
  6. XGBoost: A Scalable Tree Boosting System
  7. A Parallel Mixture of SVMs for Very Large Scale Problems
  8. A vector space model for automatic indexing
  9. Values of Non-Atomic Games
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers