/explore
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blog.alexalemi.com | ||
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jaketae.github.io
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| | | | | The other day, my friend and I were talking about our mutual friend Jeremy. "He's an oddball," my friend Sean remarked, to which I agreed. Out of nowhere, Jeremy had just told us that he would not be coming back to Korea for the next three years. "He is just about the most random person I know." And both of us, being aspiring statistics majors, began wondering: is there a systematic way of measuring randomness? It is from here that we went down the rabbit hole of Google and Wikipedia search. I ended up landing on entropy land, which is going to be the topic for today's post. It's a random post on the topic of randomness. | |
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www.quantstart.com
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| | | | | Bayesian Statistics: A Beginner's Guide | |
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blog.evjang.com
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| | | | | This is a tutorial on common practices in training generative models that optimize likelihood directly, such as autoregressive models and ... | |
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vxlabs.com
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| | | I have recently become fascinated with (Variational) Autoencoders and with PyTorch. Kevin Frans has a beautiful blog post online explaining variational autoencoders, with examples in TensorFlow and, importantly, with cat pictures. Jaan Altosaar's blog post takes an even deeper look at VAEs from both the deep learning perspective and the perspective of graphical models. Both of these posts, as well as Diederik Kingma's original 2014 paper Auto-Encoding Variational Bayes, are more than worth your time. | ||
