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Study Methodology
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How Can I Explain This to You? An Empirical Study of Deep Neural Net Explanation Methods - Spring 2021
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- 1 Intro
- 2 Outline
- 3 Motivation
- 4 Introduction
- 5 Key Contributions
- 6 Study Details
- 7 Unifying Visual Explanation Methods Across Input Domains
- 8 Saliency map
- 9 Scoped Rules (Anchors)
- 10 SHAPISHapley Additive exPlanations
- 11 A Unified Representation of Visual Explanation Frameworks
- 12 Superimposition Based Explanation Methods
- 13 Training Data Based Explanation Methods
- 14 Study Methodology
- 15 Validating Responses
- 16 Tasks & Datasets
- 17 Models and Explanations
- 18 Configuring and Optimizing Explanation Methods
- 19 Results
- 20 Usability and Stability of Explanations
- 21 Idealized vs Actualized Explanations - Superimposition Methods
- 22 Explanation-by-Example
- 23 Privacy Risks
- 24 Conclusion
- 25 Against
