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Bayesian Generative Adversarial Nets with Dropout Inference
ACM SIGKDD India Chapter
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Bayesian Networks 1 - Inference | Stanford CS221: AI (Autumn 2019)
Stanford Online
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Nikolaj Mücke (CWI) - Markov Chain Generative-Adversarial NN for Solving Bayesian Inv. Probl.
Centrum Wiskunde & Informatica
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Implementing Dropout as a Bayesian Approximation in TensorFlow
Viking Penguin
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Implementing Bayesian Inference with Neural Networks, by Zhenyu Zhu
NYU Shanghai Undergraduate Summer Research (DURF) 2017
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Adversarial Approaches to Bayesian Learning and Bayesian Approaches to Adversarial Robustness
Bayesian Deep Learning Workshop NIPS 2016
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Bayesian Inference Part I - Zoubin Ghahramani - MLSS 2015 Tübingen
Max Planck Institute for Intelligent Systems
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Bayesian Image Reconstruction using Deep Generative Models - Razvan Marinescu
Razvan Marinescu
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Bayesian Agents: Bayesian Reasoning and Deep Learning in Agent-based Systems
Bayesian Deep Learning Workshop NIPS 2016
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Ian Goodfellow: Generative Adversarial Networks (NIPS 2016 tutorial)
Steven Van Vaerenbergh
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