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Repository for the project of the course "Fondements théoriques du deep learning" of master MVA 2020

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ncaptier/MVA_BayesianBackprop

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MVA_BayesianBackprop

This code is for the project of the course "Fondements théoriques du deep learning" of master MVA 2020. We propose several numerical experiments to illustrate the methods developped in [1].

Experiments

We provide notebooks to run experiments:

Codes

In models you will find all our algorithms that we use for the experiments.

In Pyro you will find a work in progress on an implementation of the "Bayes by backprop" method in Pyro for non-linear regression.

References

[1] Charles Blundell et al. “Weight Uncertainty in Neural Networks”. In:Proceedings of the 32ndInternational Conference on International Conference on Machine Learning - Volume 37.ICML’15. Lille, France: JMLR.org, 2015, pp. 1613–1622.

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Repository for the project of the course "Fondements théoriques du deep learning" of master MVA 2020

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