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www.depthfirstlearning.com | ||
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blog.fastforwardlabs.com
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| | | | | The Variational Autoencoder (VAE) neatly synthesizes unsupervised deep learning and variational Bayesian methods into one sleek package. In Part I of this series, we introduced the theory and intuition behind the VAE, an exciting development in machine learning for combined generative modeling and inference-"machines that imagine and reason." To recap: VAEs put a probabilistic spin on the basic autoencoder paradigm-treating their inputs, hidden representations, and reconstructed outputs as probabilistic ... | |
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jxmo.io
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| | | | | A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents. | |
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yang-song.net
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| | | | | This blog post focuses on a promising new direction for generative modeling. We can learn score functions (gradients of log probability density functions) on a large number of noise-perturbed data distributions, then generate samples with Langevin-type sampling. The resulting generative models, often called score-based generative models, has several important advantages over existing model families: GAN-level sample quality without adversarial training, flexible model architectures, exact log-likelihood ... | |
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danielpecos.com
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| | | Para retomar de nuevo la marcha del blog, he decidido comenzar mostrando algunos ejemplos de programación en C#. Por el momento os dejo el obligatorio programa para todo aquel que empieza con algún lenguaje. Hola Mundo! using System; namespace HolaMundo { public class HolaMundo { public static void Main (string [] args) { Console.WriteLine ("Hola Mundo!"); } } } Sencillo, ¿verdad? Tiene mucha semejanza con Java, exceptuando que las palabras reservadas difieren y que Java no posee el concepto de espacios ... | ||
