Results 131 to 140 of about 541,400 (289)
Deep subspace clustering networks [PDF]
, 2020 We present a novel deep neural network architecture for unsupervised subspace clustering. This architecture is built upon deep auto-encoders, which non-linearly map the input data into a latent space.
Salzmann, Mathieu +4 more
core
Graph‐Laplacian modeling of spatiotemporal effects for house price estimation
Real Estate Economics, EarlyView.Abstract Many variables involve the modeling of spatial effects, and their dynamics over time. This article presents a linear model in which spatiotemporal random effects are modeled by graph‐Laplacians. A graph‐Laplacian flexibly encodes adjacency in both space and time, in our case not depending on unknown parameters. The graph‐Laplacian can be input
Willem P Sijp, Marc K. Francke
wiley +1 more source
Forecasting linear dynamical systems using subspace methods [PDF]
A new procedure to predict with subspace methods is presented in this paper. It is based on combining multiple forecasts obtained from setting a range of values for a specic parameter that is typically xed by the user in the subspace methods literature ...
Alfredo García-Hiernaux
core
Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation
Computer Graphics Forum, EarlyView.Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley +1 more source
Connectedness-based subspace clustering
, 2018 An algorithm for density-based subspace clustering of given data is proposed here. Unlike the existing density-based subspace clustering algorithms which find clusters using spatial proximity, existence of common high-density regions is the condition for
C. A. Murthy +3 more
core +1 more source
Affinification: A Fine Approximation of Deformations
Computer Graphics Forum, EarlyView.Abstract We introduce affinification, a novel method for accelerating physics‐based animation of elastic solids. During a time‐dependent simulation, our method automatically partitions the space into affine and elastic regions depending on the deformation.
A. Mercier‐Aubin +3 more
wiley +1 more source
Subspace Clustering of Physiological Data From Acute Traumatic Brain Injury Patients: Retrospective Analysis Based on the PROTECT III Trial. [PDF]
JMIR Biomed Eng, 2021 Ehsani S +4 more
europepmc +1 more source
Survey on differential estimators for 3d point clouds
Computer Graphics Forum, EarlyView.Abstract Recent advancements in 3D scanning technologies, including LiDAR and photogrammetry, have enabled the precise digital replication of real‐world objects. These methods are widely used in fields such as GIS, robotics, and cultural heritage. However, the point clouds generated by such scans are often noisy and unstructured, posing challenges for ...
Léo Arnal–Anger +4 more
wiley +1 more source
Graph-Constrained Residual Self-Expressive Subspace Clustering Network for Hyperspectral Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral images are widely use due to their rich spectral information. Meanwhile, the difficult acquisition of data labels makes unsupervised classification attracts attention.
Kun Huang +4 more
doaj +1 more source
Hierarchical Optimization of the As‐Rigid‐As‐Possible Energy
Computer Graphics Forum, EarlyView.Abstract The As‐Rigid‐As‐Possible (ARAP) energy [SA07] has become a versatile ingredient in various geometry processing and machine learning methods. The classic method for its minimization is a block coordinate descent, alternating between local rotation estimation and a global linear solve, which converges slowly for large problem instances.
Hendrik Meyer, Bernd Bickel, Marc Alexa
wiley +1 more source