Questions tagged [bayesian-deep-learning]

For questions related to Bayesian deep learning, that is, Bayesian techniques applied to deep learning models (i.e. neural networks).

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Will adding memory to a supervised learning system makes it into a Bayesian learning system?

Seung et.al recently published GameGAN paper, GameGAN learned and stored the whole Pacman game and was able to reproduce it without a game engine. The uniqueness of GameGAN is that it had added memory ...
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1answer
32 views

Is there any research on models that provide uncertainty estimation?

Is there any research on machine learning models that provide uncertainty estimation? If I train a denoising autoencoder on words and put through a noised word, I'd like it to return a certainty that ...
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Are bayesian neural networks suited for text (or document) classification?

I've tried to do my research on Bayesian neural networks online, but I find most of them are used for image classification. This is probably due to the nature of Bayesian neural networks, which may be ...
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1answer
564 views

How should the neural network deal with unexpected inputs?

I recently wrote an application using a deep learning model designed to classify inputs. There are plenty of examples of this using images of irises, cats, and other objects. If I trained a data ...
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6answers
9k views

Why do CNN's sometimes make highly confident mistakes, and how can one combat this problem?

I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I'm feeding in a bunch of handwritten digits, and non-digits from a document. I want the CNN to report errors, so I ...
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1answer
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How can supervised learning be viewed as a conditional probability of the labels given the inputs?

In the literature and textbooks, one often sees supervised learning expressed as a conditional probability, e.g., $\ \ \ \ \ \rho(\vec{y}|\vec{x},\vec{\theta})$ where $\vec{\theta}$ denotes a ...