A novel FlowViT-Diff framework that integrates a Vision Transformer (ViT) with an enhanced denoising diffusion probabilistic model (DDPM) for super-resolution reconstruction of high-resolution flow ...

The development of large language models (LLMs) is entering a pivotal phase with the emergence of diffusion-based architectures. These models, spearheaded by Inception Labs through its new Mercury ...

Stanford University’s Deep Generative Models (XCS236) is a graduate-level, professional online course offered by the Stanford ...

Inception, a new Palo Alto-based company started by Stanford computer science professor Stefano Ermon, claims to have developed a novel AI model based on “diffusion” technology. Inception calls it a ...

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as ...

Previous high-order solvers are unstable for guided sampling: Samples use the pre-trained DPMs on ImageNet 256 256 with a classifier guidance scale 8.0, varying different samplers (and different ...

With so much money flooding into AI startups, it’s a good time to be an AI researcher with an idea to test out. And if the idea is novel enough, it might be easier to get the resources you need as an ...

All over the AI field, teams are unlocking new functionality by changing the ways that the models work. Some of this has to do with input compression and changing the memory requirements for LLMs, or ...