How to handle Uncertainty in Deep Learning #2.1

▬▬ Useful Resources / Papers ▬▬▬▬▬
Bayesian Methods for Hackers: https://github.com/CamDavidsonPilon/P...
Regularization as bayesian prior: https://rohanvarma.me/Regularization/
Variational Inference Blogpost: http://krasserm.github.io/2019/03/14/...
Bayesian Neural Networks Blogpost: https://www.cs.toronto.edu/~duvenaud/...
Dropout as Bayesian Approximation: https://arxiv.org/pdf/1506.02142.pdf
Deep Ensembles as Approximate Bayesian inference: https://cims.nyu.edu/~andrewgw/deepen...

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All icons from flaticon by Freepik and Vectors Tank

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ArtHouse Studio from Pexels

▬▬ Timestamps ▬▬▬▬▬▬▬▬▬▬▬
00:00 Introduction
00:21 Frequentism vs. Bayesiansim
01:50 Bayesian Neural Networks
03:36 BNNs and Bayes Rule
06:12 Variational Inference
08:11 VI in BNNs
09:41 Monte Carlo Dropout
11:48 Deep Ensembles
13:05 Outro


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