而Stable Diffusion正是为解决图像扩散模型的速度难题而设计的。 4.1 表征(Latent)扩散模型 Stable Diffusion是一个表征扩散模型。它首先把图像压缩到表征空间,以避免在高维的图像空间进行操作。这就快多了。 4.2 图像表征和复原 图像到表征和表征到图像的转换是通过VAE(Variational Autoencoder)来实现的。 VAE包括encode...
Stable Diffusion, however, has its own trick to deal with high-dimensionality. Instead of working with images, its autoencoder element turns them into low-dimension representations. There’s still noise, timesteps, and prompts, but all the U-Net’s processing is done in a compressed latent sp...
In contrast, Stable Diffusion is an open-sourcelatent diffusion modelthat uses text or image prompts to encode a latent representation of the desired image. The latent representation guides the diffusion process to ensure the generated image is statistically similar to the user’s prompt. Midjourney...
theR2is not interchangeable with the correlation coefficient squared. All predictions were performed using linear ridge regression as it showed a favourable ratio of computation time to accuracy in previous work104and preliminary
Diffusion models:Also known as denoising diffusion probabilistic models (DDPMs), diffusion models are generative models that determine vectors in latent space through a two-step process during training. The two steps are forward diffusion and reverse diffusion. The forward diffusion process slowly adds...
Our team thoroughly evaluated the improvements in the common ImageNet-512 setting using latent diffusion and reached a record FID of 1.81 in this widely used benchmark. However, simply looking at the bottom line number could be misleading. What matters is the scaling with size. ...
In current years, the improvement of deep learning has brought about tremendous changes: As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) have been widely employed in various fields including transportation. This
At the heart of Sora is DiT (diffusion transformer), a model that leverages the scaling capabilities of transformers alongside the iterative refinement process of diffusion models. Transformers, known for their effectiveness in handling sequential data, provide a robust architecture for modeling the temp...
A recently-popular class of latent variable models called diffusion models, can be used for a number of tasks including image denoising, inpainting, super-resolution upscaling, and image generation. This technique helped start the popularization of generative AI. For example, an image generation model...
Although latent variables as causal entities are not appealed to within behavior analysis, this does not mean that concepts like implicit bias or attitudes are not amenable to study from a behavioral perspective. For instance, De Houwer (2019) recently argued that implicit bias (or “attitudes”)...