Quantum computers—devices that process information using quantum mechanical effects—have long been expected to outperform ...

Abstract: Scene perception based on 3-D reconstruction has been widely applied in various downstream applications for intelligent devices. The use of deep learning methods for scene perception has ...

Stephen Whitelam, a researcher whose work spans thermodynamic theory and machine learning, has described a framework for ...

Molecular glues are enjoying the spotlight, but discovering new ones is often a matter of luck. A new method, developed by ...

Interstitial fluid mirrors many biomarkers found in blood and has attracted growing interest as a target for painless diagnostics. Microneedles offer a way to access this fluid through the skin, but ...

Discrete diffusion language models (dLLMs) have recently emerged as a promising alternative to traditional autoregressive approaches, offering the flexibility to generate tokens in arbitrary orders ...

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 ...

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 ...

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.