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astroautomata.com | ||
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tiao.io
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| | | | | An in-depth practical guide to variational encoders from a probabilistic perspective. | |
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iclr-blogposts.github.io
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| | | | | The transfer of matching-based training from Diffusion Models to Normalizing Flows allows to fit expressive continuous normalizing flows efficiently and therefore enables their usage for different kinds of density estimation tasks. One particularly interesting task is Simulation-Based Inference, where Flow Matching enabled several improvements. The post shall focus on the discussion of Flow Matching for Continuous Normalizing Flows. To highlight the relevance and the practicality of the method, their use and advantages for Simulation-Based Inference is elaborated. | |
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stribny.name
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| | | | | Fields in Artificial Intelligence and what libraries to use to address them. | |
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golb.hplar.ch
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| | | [AI summary] The article describes the implementation of a neural network in Java and JavaScript for digit recognition using the MNIST dataset, covering forward and backpropagation processes. | ||
