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Found 4 papers, 1 papers with code
Hyper-Diffusion: Estimating Epistemic and Aleatoric Uncertainty with a Single Model
In this work we introduce a new approach to ensembling, hyper-diffusion, which allows one to accurately estimate epistemic and aleatoric uncertainty with a single model.
Generative Novel View Synthesis with 3D-Aware Diffusion Models
We present a diffusion-based model for 3D-aware generative novel view synthesis from as few as a single input image.
SUD$^2$: Supervision by Denoising Diffusion Models for Image Reconstruction
Many imaging inverse problems$\unicode{x2014}$such as image-dependent in-painting and dehazing$\unicode{x2014}$are challenging because their forward models are unknown or depend on unknown latent parameters.
Efficient Geometry-aware 3D Generative Adversarial Networks
Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge.
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