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- Probabilistic learning
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Classroom Contents
Evidential Deep Learning and Uncertainty
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- 1 - Introduction and motivation
- 2 - Outline for lecture
- 3 - Probabilistic learning
- 4 - Discrete vs continuous target learning
- 5 - Likelihood vs confidence
- 6 - Types of uncertainty
- 7 - Aleatoric vs epistemic uncertainty
- 8 - Bayesian neural networks
- 9 - Beyond sampling for uncertainty
- 10 - Evidential deep learning
- 11 - Evidential learning for regression and classification
- 12 - Evidential model and training
- 13 - Applications of evidential learning
- 14 - Comparison of uncertainty estimation approaches
- 15 - Conclusion
