MIT Introduction to Deep Learning 6.S191: Lecture 6 with Ava Soleimany.
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Lecture Outline
- 0:00 – Introduction
- 0:58 – Course logistics
- 3:59 – Upcoming guest lectures
- 5:35 – Deep learning and expressivity of NNs
- 10:02 – Generalization of deep models
- 14:14 – Adversarial attacks
- 17:00 – Limitations summary
- 18:18 – Structure in deep learning
- 22:53 – Uncertainty & bayesian deep learning
- 28:09 – Deep evidential regression
- 33:08 – AutoML
- 36:43 – Conclusion
