Below are some random examples (at 256 resolution) from a 100MM model trained from scratch for 260k iterations (about 32 hours on 1 A100): If you have your own dataset of URLs + captions, the process ...
Project Overview This project focuses on generating conditional time series data, specifically for streamflow (SF) prediction in gauged and ungauged basins. Accurate streamflow forecasting is crucial ...
Scientists at Insilico Medicine have introduced Precious2GPT, an innovative multimodal architecture that integrates the pretrained transformer and conditional diffusion for generating and predicting ...
Abstract: Diffusion Transformer (DiT), an emerging diffusion model for visual generation, has demonstrated superior perfor mance but suffers from substantial computational costs. Our investigations ...
Researchers at New York University have developed a new architecture for diffusion models that improves the semantic representation of the images they generate. “Diffusion Transformer with ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results