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christopher-beckham.github.io
| | blog.ml.cmu.edu
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| | The latest news and publications regarding machine learning, artificial intelligence or related, brought to you by the Machine Learning Blog, a spinoff of the Machine Learning Department at Carnegie Mellon University.
| | fa.bianp.net
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| | The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ...
| | jxmo.io
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| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | www.paepper.com
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| Recent advances in training deep neural networks have led to a whole bunch of impressive machine learning models which are able to tackle a very diverse range of tasks. When you are developing such a model, one of the notable downsides is that it is considered a "black-box" approach in the sense that your model learns from data you feed it, but you don't really know what is going on inside the model.