Abstract: This paper primarily explores the potential of denoising diffusion probabilistic models in generating vibration signals for planetary gear systems, producing data under two different health ...

LDP consists of a diffusion modeling for encoded text space of an off-the-shelf pre-trained encoder and decoder, the diffusion process can be intervened by additional controller . Paraphrase ...

There is a mismatch between the loaded weights and the generated models. There are extra attention blocks in the loaded weights that are not present in the model. As config files I'm using the default ...

Diffusion model inferers class will move away from inferers.py. All the tutorials querying these will have to shift from the original inferers.py class to the new one.

AMD has officially enabled Stable Diffusion on its latest generation of Ryzen AI processors, bringing local generative AI image creation to systems equipped with XDNA 2 NPUs. The feature arrives ...

In recent months, there has been growing interest in applying diffusion models—originally designed for continuous data, such as images—to natural language processing tasks. This has led to the ...

Abstract: Diffusion tensor imaging (DTI) is a significant non-invasive neuroimaging technique with valuable applications in clinical medicine. To address the lengthy acquisition times and high costs ...

We present the vector quantized diffusion (VQ-Diffusion) model for text-to-image generation. This method is based on a vector quantized variational autoencoder (VQ-VAE) whose latent space is modeled ...