Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...

This project provides a complete pipeline for latent diffusion models, covering image dataset encoding into latents, training three different models with two distinct noise schedules, and sampling ...

English look at AI and the way its text generation works. Covering word generation and tokenization through probability scores, to help ...

Abstract: Hyperspectral images (HSIs) and multispectral images (MSIs) fusion is a hot topic in the remote sensing society. A high-resolution HSI (HR-HSI) can be obtained by fusing a low-resolution HSI ...

byPhotosynthesis Technology: It's not just for plants! @photosynthesis Cultivating life through Photosynthesis, harnessing sunlight to nourish ecosystems and fuel a sustainable future. Cultivating ...

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 ...

Faster inference: frequency-aware diffusion sampling strategy. The frequency progression property of FAR also inspires us to employ fewer diffusion sampling steps for lower frequency levels, as ...

Abstract: Diffusion models have demonstrated impressive generative capabilities in various computer vision tasks, providing a novel technological approach to the study of multimodal image fusion.

Diffusion processes have emerged as promising approaches for sampling from complex distributions but face significant challenges when dealing with multimodal targets. Traditional methods based on ...