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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes

February 1, 2023

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Authors

Ranganath Krishnan

Intel Labs


Mahesh Subedar

Intel Labs


Omesh Tickoo

Intel Labs


DOI:

10.1609/aaai.v34i04.5875


Abstract:

Stochastic variational inference for Bayesian deep neural network (DNN) requires specifying priors and approximate posterior distributions over neural network weights. Specifying meaningful weight priors is a challenging problem, particularly for scaling variational inference to deeper architectures involving high dimensional weight space. We propose MOdel Priors with Empirical Bayes using DNN (MOPED) method to choose informed weight priors in Bayesian neural networks. We formulate a two-stage hierarchical modeling, first find the maximum likelihood estimates of weights with DNN, and then set the weight priors using empirical Bayes approach to infer the posterior with variational inference. We empirically evaluate the proposed approach on real-world tasks including image classification, video activity recognition and audio classification with varying complex neural network architectures. We also evaluate our proposed approach on diabetic retinopathy diagnosis task and benchmark with the state-of-the-art Bayesian deep learning techniques. We demonstrate MOPED method enables scalable variational inference and provides reliable uncertainty quantification.

Topics: AAAI

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HOW TO CITE:

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes Proceedings of the AAAI Conference on Artificial Intelligence (2020) 4477-4484.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes AAAI 2020, 4477-4484.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo (2020). Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. Proceedings of the AAAI Conference on Artificial Intelligence, 4477-4484.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo. Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.4477-4484.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo. 2020. Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. "Proceedings of the AAAI Conference on Artificial Intelligence". 4477-4484.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo. (2020) "Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes", Proceedings of the AAAI Conference on Artificial Intelligence, p.4477-4484

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo, "Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes", AAAI, p.4477-4484, 2020.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo. "Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.4477-4484.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo. "Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 4477-4484.

Ranganath Krishnan||Mahesh Subedar||Omesh Tickoo. Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes. AAAI[Internet]. 2020[cited 2023]; 4477-4484.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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