Jun 25, 2015 · In this paper, we propose a manifold learning algorithm based on deep learning to create an encoder, which maps a high-dimensional dataset and ...

The diffusion net enables to perform outlier detection, indicating when the extension of a given point via the encoder is faulty due to its being an outlier ...

DiffusionNet is a general-purpose method for deep learning on surfaces such as 3D triangle meshes and point clouds. It is well-suited for tasks like ...

Dec 1, 2020 · We introduce a new general-purpose approach to deep learning on 3D surfaces, based on the insight that a simple diffusion layer is highly effective for spatial ...

Diffusion models, also known as diffusion probabilistic models or score-based generative models, are a class of latent variable generative models.

Aug 31, 2017 · Non-linear manifold learning enables high-dimensional data analysis, but requires out-of-sample-extension methods to process new data points ...

They are usually referred to as a grip single or a grip double. The single usually has a green border and the double has a red border. The Single is usually one ...

This work considers learning a non-linear embedding of data into Euclidean space as a way to improve the hierarchical clustering produced by agglomerative ...

Apr 2, 2023 · This article explains ControlNet Features and Provided a Step by Step Guide to use ControlNet on Automatic 1111 Stable Diffusion Interface.