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jamie-wong.com
| | thenumb.at
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| | [latexpage] In this blog-post we will have a look at how Differential Equations (DE) can be solved numerically via the Finite Differences method. By solving differential equations we can run simula...
| | andrewkchan.dev
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| | eigenfoo.xyz
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| My current project involves working with deep autoregressive models: a class of remarkable neural networks that aren't usually seen on a first pass through deep learning. These notes are a quick write-up of my reading and research: I assume basic familiarity with deep learning, and aim to highlight general trends and similarities across autoregressive models, instead of commenting on individual architectures. tldr: Deep autoregressive models are sequence models, yet feed-forward (i.e. not recurrent); generative models, yet supervised. They are a compelling alternative to RNNs for sequential data, and GANs for generation tasks.