Local Explanations for Deep Learning Models - Fall 2023

Local Explanations for Deep Learning Models - Fall 2023

UofU Data Science via YouTube Direct link

Prompting (Part 2); Evaluation of Free-Text Explanations

5 of 16

5 of 16

Prompting (Part 2); Evaluation of Free-Text Explanations

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Local Explanations for Deep Learning Models - Fall 2023

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  1. 1 Course overview and logistics
  2. 2 Data Preparation & Transformer
  3. 3 Pretrain-Finetune; Uncertainty Estimation (Part 1)
  4. 4 Uncertainty (Part 2); Prompting; Chain-of-Thoughts
  5. 5 Prompting (Part 2); Evaluation of Free-Text Explanations
  6. 6 Gradient-based Input Attribution
  7. 7 Evaluation of Input Attribution
  8. 8 Select-then-Predict
  9. 9 Pairwise Feature Importance (Effective Attention)
  10. 10 Data Influence
  11. 11 Contrastive Explanations
  12. 12 Application-Grounded Evaluations of Explanations
  13. 13 Human Trust in AI
  14. 14 Challenges in Fostering (Dis)Trust in AI
  15. 15 Explainability as a Dialog
  16. 16 An Overview of Local Explainability Methods & Their Evaluation

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