[Paper Review] VI/BNN/NF paper 31~40
I have summarized the must read + advanced papers of papers regarding….
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various methods using Variational Inference
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Bayesian Neural Network
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Probabilistic Deep Learning
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Normalizing Flows
31.Uncertainty Estimations by Softplus normalization in Bayesian Convolutional Neural Networks with Variational Inference
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32.MADE ; Masked Autoencoder for Distribution Estimation
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33.Improved Variational Inference with Inverse Autoregressive Flow (2016)
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34.Masked Autoregressive Flow for Density Estimation (2017)
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35.A Stochastic Decoder for Neural Machine Translation (2018)
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36.Gaussian Process for Big Data (2013)
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37.Adversarial Autoencoders (2016)
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38. Practical Deep Learning with Bayesian Principles (2019)
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39.Autoencoding Variational Inference for Topic Models (2017)
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40.Topic Modeling in Embedding Spaces (2019)
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