Oscar Gomez

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Oscar Gomez trusts overall

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

  1. David Martens
  2. Scott M. Lundberg
  3. Yao Ming
  4. Paolo Tamagnini
  5. Xun Zhao
  6. Jiawei Zhang
  7. James Wexler
  8. Josua Krause
  9. Foster J. Provost
  10. Su-In Lee

Who trusts Oscar Gomez overall

  1. Jianlong Zhou
  2. Amir H. Gandomi

Papers from Oscar Gomez's perspective

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

  1. A Unified Approach to Interpreting Model Predictions
  2. A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations
  3. Explaining Data-Driven Document Classifications
  4. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
  5. Explanation in Artificial Intelligence: Insights from the Social Sciences
  6. Et al
  7. Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models
  8. The mythos of model interpretability
  9. RuleMatrix: Visualizing and Understanding Classifiers with Rules
  10. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Their papers