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A variational autoencoder is a generative model with a prior and noise distribution respectively. Usually such models are trained using the expectation-maximization meta-algorithm (e.g. probabilistic PCA , (spike & slab) sparse coding).
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.
This can be understood as a "decoding" process, whereby every latent vector is a code for an image , and the generator performs the decoding. This naturally leads to the idea of training another network that performs "encoding", creating an autoencoder out of the encoder-generator pair.
In 2014, advancements such as the variational autoencoder and generative adversarial network produced the first practical deep neural networks capable of learning generative models, as opposed to discriminative ones, for complex data such as images. These deep generative models were the first to output not only class labels for images but also ...
Stable Diffusion consists of 3 parts: the variational autoencoder (VAE), U-Net, and an optional text encoder. [17] The VAE encoder compresses the image from pixel space to a smaller dimensional latent space , capturing a more fundamental semantic meaning of the image. [ 16 ]
The implementation of chords using particular tunings is a defining part of the literature on guitar chords, which is omitted in the abstract musical-theory of chords for all instruments. For example, in the guitar (like other stringed instruments but unlike the piano ), open-string notes are not fretted and so require less hand-motion.
Code Chord type Major: Major chord: Minor: Minor chord: Augmented: Augmented chord: Diminished: ... List of musical chords Name Chord on C Sound # of p.c.-Forte # p.c ...
It has a relatively large codebase; as of March 10, 2017, the source includes over 600,000 lines of C++, 140,000 lines of Scheme, and 120,000 lines of Python code. [ 13 ] It uses a simple text notation for music input, which LilyPond interprets and processes in a series of stages. [ 14 ]