A variational autoencoder is a specific type of neural network that helps to generate complex models based on data sets. In general, autoencoders are often talked about as a type of deep learning network that tries to reconstruct a model or match the target outputs to provided inputs through...
An autoencoder is a neural network trained to efficiently compress input data down to essential features and reconstruct it from the compressed representation.
What Does Autoencoder Mean? An autoencoder (AE) is a specific kind of unsupervised artificial neural network that provides compression and other functionality in the field of machine learning. The specific use of the autoencoder is to use a feedforward approach to reconstitute an output from an...
The first image is the AI Image, the second is real and is attributed to Image by wirestock on Freepik. Variational Autoencoders (VAEs) To explain variational autoencoders let's look at a similar but slightly different example and implementation. Let’s say that instead of trying to deter...
What exactly is generative AI? Salesforce's Chief Scientist explains how this technology is changing the future for us all.
Variational autoencoders (VAEs): VAEs consist of two neural networks typically referred to as the encoder and decoder.When given an input, an encoder converts it into a smaller, more dense representation of the data. This compressed representation preserves the information that’s needed for a...
Variational autoencodersor VAEs, which were introduced in 2013, and enabled models that could generate multiple variations of content in response to a prompt or instruction. Diffusion models, first seen in 2014, which add "noise" to images until they are unrecognizable, and then remove the nois...
Variational autoencoders (VAEs): VAEs represent another type of generative model that leverages the principles of statistical inference. They work by encoding input data into a latent space (a compressed representation of the data) and then decoding this latent representation to generate new data....
Variational Autoencoders (VAEs): VAEs are another kind of AI model that can create lifelike images and text. They encode data into a special space, capturing key features. This encoded space allows VAEs to generate new data similar to what they’ve learned. Transformers: Transformers repr...
While GANS and transformers are among the most popular generative AI models, several other techniques are used as well, such as variational autoencoders (VAEs), which also rely on two neural networks to generate new data based on sample data, and neural radiance fields (NeRFs), which is bei...