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Metric-constrained Eikonal solver
The dataset used in this paper is a collection of manifolds, including Euclidean space, the unit hypersphere, and the peaks manifold. -
Manifold Learning
The dataset used in the paper is a finite pseudometric space with n points, and the goal is to construct an n x m real-valued matrix of embeddings. -
Tangent Bundle Neural Networks
The dataset is used to test the performance of Tangent Bundle Neural Networks on three tasks: denoising of a tangent vector field on the torus, reconstruction from partial... -
2D Spiral Dataset
The dataset used in the paper is a 2D spiral dataset, which is a classic manifold learning dataset. -
Commutativity and Disentanglement from the Manifold Perspective
The dataset is used to study disentanglement from the manifold perspective. -
Swiss Roll dataset
The dataset used in the paper is a 3D non-linear Swiss Roll dataset which comprises 1600 datapoints grouped in 4 classes. -
LOCA: LOcal Conformal Autoencoder
The LOCA dataset is a collection of distorted neighborhoods of a fixed size of data samples. -
Coil-10 dataset
The Coil-10 dataset is a 3D dataset of 10 physical objects rotating along one axis in 3D. The dataset is used to test the proposed chart autoencoder model. -
First hitting diffusion models
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a first hitting diffusion model for generating manifold, graph and... -
Estimating visual information from audio through manifold learning
Estimating visual information from audio through manifold learning. -
Target Measure Diffusion Map
The dataset used in this paper is a point cloud X (n) sampled from a density ρ using any suitable enhanced sampling technique such as temperature acceleration or metadynamics.
