Ge Gao

Computer Vision and Pattern Recognition · with Chen · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ge Gao trusts overall

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

  1. Raymond Reiter
  2. Josua Krause
  3. Tania Lombrozo

Papers from Ge Gao's perspective

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

  1. Visualizing and Understanding Convolutional Networks
  2. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
  3. The mythos of model interpretability
  4. Towards A Rigorous Science of Interpretable Machine Learning
  5. Explanation in Artificial Intelligence: Insights from the Social Sciences
  6. Interacting with Predictions: Visual Inspection of Black-box Machine Learning Models
  7. European Union Regulations on Algorithmic Decision-Making and a "Right to Explanation"
  8. Some observations on mental models
  9. Causal-explanatory pluralism: How intentions, functions, and mechanisms influence causal ascriptions.
  10. Intelligibility and Accountability: Human Considerations in Context-Aware Systems

Their papers