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christopher-beckham.github.io | ||
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sander.ai
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| | | | | The noise schedule is a key design parameter for diffusion models. Unfortunately it is a superfluous abstraction that entangles several different model aspects. Do we really need it? | |
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dm13450.github.io
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| | | | | The Almgren Chris model from Optimal Execution of Portfolio Transactions is the most well known optimal execution model and provides the foundational math about how to think about trading some quantity of an asset. This blog post goes through the math and how we set the problem up and arrived at the various solutions. | |
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www.nicktasios.nl
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| | | | | In the Latent Diffusion Series of blog posts, I'm going through all components needed to train a latent diffusion model to generate random digits from the MNIST dataset. In the third, and last, post, | |
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marcospereira.me
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| | | In this post we summarize the math behind deep learning and implement a simple network that achieves 85% accuracy classifying digits from the MNIST dataset. | ||
