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NeuralSpace is a unique blend of people staying close to research that share the passion of making AI available for everyone. We create the ecosystem that allows you to use AI without worrying about the complex algorithms powering it.
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Bayesian Neural Network Series Post 2: Background Knowledge
Bayesian Neural Network Series Post 2: Background Knowledge
This post is the second post in an eight-post series of Bayesian Convolutional Networks. The posts will be structured as follows:
Kumar Shridhar
Jan 18
Bayesian Neural Network Series Post 1: Need for Bayesian Networks
Bayesian Neural Network Series Post 1: Need for Bayesian Networks
This post is the first post in an eight-post series of Bayesian Convolutional Networks. The posts will be structured as follows:
Kumar Shridhar
Jan 2
Bayesian Convolutional Neural Networks with Bayes by Backprop
Bayesian Convolutional Neural Networks with Bayes by Backprop
So far, we have elaborated how Bayes by Backprop works on a simple feedforward neural network. In this post, I will explain how you can…
Felix Laumann
Dec 12, 2018
How Bayesian methods embody Occam’s razor
How Bayesian methods embody Occam’s razor
Some of you might have heard the term Occam’s razor, sometimes spelled Ockham’s razor, together with Bayesian methods. It is indeed a…
Felix Laumann
Nov 26, 2018
When machine learning meets complexity: why Bayesian deep learning is unavoidable
When machine learning meets complexity: why Bayesian deep learning ...
By now, all of you have probably followed deep learning research for quite a while. In 1998, LeCun et al. proposed the very simple MNIST…
Felix Laumann
Nov 26, 2018
Inference in Probabilistic Models: Monte Carlo and variational methods
Inference in Probabilistic Models: Monte Carlo and variational methods
In this post, we’ll elaborate on the two major school of thoughts how we can approximate an intractable function in probabilistic models…
Felix Laumann
Jul 11, 2018
Probabilistic Deep Learning: Bayes by Backprop
Probabilistic Deep Learning: Bayes by Backprop
Having understood all the fundamentals, we can now proceed and apply them to deep learning. If you cannot follow my steps here, please go…
Felix Laumann
Jul 5, 2018
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