Cover Image

Atlas Gaussian processes on restricted domains and point clouds

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Niu, Mu, Zhang, Yue, Ye, Ke, Cheung, Pokman, Wang, Yizhu, Yang, Xiaochen
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Intrinsic Gaussian Processes on Manifolds and Their Accelerations by Symmetry
by: Ye, Ke, et al.
Published: (2020)

Graph Pooling by Local Cluster Selection
by: Chen, Yizhu
Published: (2024)

DiffImpute: Tabular Data Imputation With Denoising Diffusion Probabilistic Model
by: Wen, Yizhu, et al.
Published: (2024)

Scalable mixed-domain Gaussian process modeling and model reduction for longitudinal data
by: Timonen, Juho, et al.
Published: (2021)

Sparse discovery of differential equations based on multi-fidelity Gaussian process
by: Meng, Yuhuang, et al.
Published: (2024)

Modeling high dimensional point clouds with the spherical cluster model
by: Cazals, Frédéric, et al.
Published: (2025)

FGM optimization in complex domains using Gaussian process regression based profile generation algorithm
by: Konda, Chaitanya Kumar, et al.
Published: (2025)

Interpretable Feature Interaction via Statistical Self-supervised Learning on Tabular Data
by: Zhang, Xiaochen, et al.
Published: (2025)

Geographical hotspot prediction based on point cloud-voxel-community partition clustering
by: Tang, Yan
Published: (2025)

Gaussian process learning of nonlinear dynamics
by: Ye, Dongwei, et al.
Published: (2023)

The BdryMatérn GP: Reliable incorporation of boundary information on irregular domains for Gaussian process modeling
by: Ding, Liang, et al.
Published: (2025)

Classifying point clouds at the facade-level using geometric features and deep learning networks
by: Tan, Yue, et al.
Published: (2024)

Deep graph kernel point processes
by: Dong, Zheng, et al.
Published: (2023)

Energy Score-Guided Neural Gaussian Mixture Model for Predictive Uncertainty Quantification
by: Yang, Yang, et al.
Published: (2026)

Tighter sparse variational Gaussian processes
by: Bui, Thang D., et al.
Published: (2025)

Inferring manifolds using Gaussian processes
by: Dunson, David B, et al.
Published: (2021)

Knockoff-Guided Compressive Sensing: A Statistical Machine Learning Framework for Support-Assured Signal Recovery
by: Zhang, Xiaochen, et al.
Published: (2025)

Guidance with Spherical Gaussian Constraint for Conditional Diffusion
by: Yang, Lingxiao, et al.
Published: (2024)

Reconstructing the local density field with combined convolutional and point cloud architecture
by: Barthe-Gold, Baptiste, et al.
Published: (2025)

PUAL: A Classifier on Trifurcate Positive-Unlabeled Data
by: Wang, Xiaoke, et al.
Published: (2024)

Cross-modal feature fusion for robust point cloud registration with ambiguous geometry
by: Wang, Zhaoyi, et al.
Published: (2025)

SaliencyI2PLoc: saliency-guided image-point cloud localization using contrastive learning
by: Li, Yuhao, et al.
Published: (2024)

Infinite Neural Operators: Gaussian processes on functions
by: de Souza, Daniel Augusto, et al.
Published: (2025)

Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems
by: Yang, Xianjin, et al.
Published: (2025)

AtlasD: Automatic Local Symmetry Discovery
by: Bhat, Manu, et al.
Published: (2025)

PDE-constrained Gaussian process surrogate modeling with uncertain data locations
by: Ye, Dongwei, et al.
Published: (2023)

Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination
by: Bai, Yuchen, et al.
Published: (2023)

LucidAtlas: Learning Uncertainty-Aware, Covariate-Disentangled, Individualized Atlas Representations
by: Jiao, Yining, et al.
Published: (2025)

Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term
by: Yue, Yun, et al.
Published: (2023)

HeRB: Heterophily-Resolved Structure Balancer for Graph Neural Networks
by: Chen, Ke-Jia, et al.
Published: (2025)

Distributional encoding for Gaussian process regression with qualitative inputs
by: Da Veiga, Sébastien
Published: (2025)

Gradient-enhanced deep Gaussian processes for multifidelity modelling
by: Bone, Viv, et al.
Published: (2024)

On the Gaussian process limit of Bayesian Additive Regression Trees
by: Petrillo, Giacomo
Published: (2024)

Stationarity without mean reversion in improper Gaussian processes
by: Ambrogioni, Luca
Published: (2023)

Verifiable cloud-based variational quantum algorithms
by: Yang, Junhong, et al.
Published: (2024)

GK-SMOTE: A Hyperparameter-free Noise-Resilient Gaussian KDE-Based Oversampling Approach
by: Miraj, Mahabubur Rahman, et al.
Published: (2025)

Byzantine-resilient federated online learning for Gaussian process regression
by: Zhang, Xu, et al.
Published: (2025)

Evaluating saliency scores in point clouds of natural environments by learning surface anomalies
by: Arav, Reuma, et al.
Published: (2024)

Reconstructing facade details using MLS point clouds and Bag-of-Words approach
by: Froech, Thomas, et al.
Published: (2024)

Scalable Gaussian process modeling of parametrized spatio-temporal fields
by: Dama, Srinath, et al.
Published: (2026)