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almostsuremath.com
| | nickhar.wordpress.com
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| | 1. Low-rank approximation of matrices Let $latex {A}&fg=000000$ be an arbitrary $latex {n \times m}&fg=000000$ matrix. We assume $latex {n \leq m}&fg=000000$. We consider the problem of approximating $latex {A}&fg=000000$ by a low-rank matrix. For example, we could seek to find a rank $latex {s}&fg=000000$ matrix $latex {B}&fg=000000$ minimizing $latex { \lVert A - B...
| | ggcarvalho.dev
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| | Using the power of randomness to answer scientific questions.
| | jxmo.io
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| | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.
| | solid-angle.blogspot.com
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| Programmers don't generally have reels, but we do have blogs. I've been explaining the rendering work I did on BioShock Infinite quite a b...