"Structured probabilistic inference and generative modeling." "Classical diffusion models incrementally add small, Gaussian noise (a normal random variable with a small amplitude) to transform the ...

Stable Diffusion operates using a process known as diffusion modeling, a technique based on probabilistic generative modeling. The model begins with a noisy image and gradually refines it ...

The image generator from GPT-4o impresses with its quality and precise text integration. But what makes it different from ...

The current study introduces a probabilistic framework to explicitly model the correlation between diffusion trajectories, offering the first formal basis for understanding and improving diffusion ...

By deriving how often a bacterium transitions between surface states, Mattingly could determine the probability ... diffusion of passive substances like dyes, he was able to construct a model ...

Cell aging has always been an important topic in biological research, and telomere shortening is one of the key issues in cell aging studies.

Pixel-level discrepancies over a long time span decrease caption accuracy. To address these problems, we propose a probabilistic diffusion-based model that leverages its remarkable generative ...

Experiments run on Google Cloud TPU v3-8. Requires TensorFlow 1.15 and Python 3.5, and these dependencies for CPU instances (see requirements.txt): pip3 install fire ...

In response to this challenge, this paper proposes a high-resolution TWS imaging method by the conditional denoising diffusion probabilistic model (DDPM). First, we design a hybrid encoder to extract ...