Cover Image

Kriging via variably scaled kernels

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Audone, Gianluca, Marchetti, Francesco, Perracchione, Emma, Rossini, Milvia
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Rational Kriging
by: Joseph, V. Roshan
Published: (2023)

Feature Understanding and Sparsity Enhancement via 2-Layered kernel machines (2L-FUSE)
by: Camattari, Fabiana, et al.
Published: (2025)

A Recipe for Learning Variably Scaled Kernels via Discontinuous Neural Networks
by: Audone, Gianluca, et al.
Published: (2024)

A fast and effective kernel two-sample test for large-scale data
by: Song, Hoseung, et al.
Published: (2021)

Optimal differentially private kernel learning with random projection
by: Lee, Bonwoo, et al.
Published: (2025)

Greedy feature selection: Classifier-dependent feature selection via greedy methods
by: Camattari, Fabiana, et al.
Published: (2024)

Causal Discovery in Multivariate Time Series through Mutual Information Featurization
by: Paldino, Gian Marco, et al.
Published: (2025)

The co-varying ties between networks and item responses via latent variables
by: Wang, Selena, et al.
Published: (2024)

Score matching through the roof: linear, nonlinear, and latent variables causal discovery
by: Montagna, Francesco, et al.
Published: (2024)

Treatment response as a latent variable
by: Tosh, Christopher, et al.
Published: (2025)

Conformal Prediction: a Unified Review of Theory and New Challenges
by: Fontana, Matteo, et al.
Published: (2020)

Selective Induction Heads: How Transformers Select Causal Structures In Context
by: D'Angelo, Francesco, et al.
Published: (2025)

Flexible variable selection in the presence of missing data
by: Williamson, B. D., et al.
Published: (2022)

Reducing the dimensionality and granularity in hierarchical categorical variables
by: Wilsens, Paul, et al.
Published: (2024)

Fast kernel methods: Sobolev, physics-informed, and additive models
by: Doumèche, Nathan, et al.
Published: (2025)

Sparse-group boosting -- Unbiased group and variable selection
by: Obster, Fabian, et al.
Published: (2022)

Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
by: You, Kisung
Published: (2026)

MMM: Clustering Multivariate Longitudinal Mixed-type Data
by: Amato, Francesco, et al.
Published: (2025)

Extremal graphical modeling with latent variables via convex optimization
by: Engelke, Sebastian, et al.
Published: (2024)

Fusion of classical and quantum kernels enables accurate and robust two-sample tests
by: Terada, Yu, et al.
Published: (2025)

Compactly-supported nonstationary kernels for computing exact Gaussian processes on big data
by: Risser, Mark D., et al.
Published: (2024)

Unsupervised Attributed Dynamic Network Embedding with Stability Guarantees
by: Ceccherini, Emma, et al.
Published: (2025)

What is in the model? A Comparison of variable selection criteria and model search approaches
by: Xu, Shuangshuang, et al.
Published: (2025)

Debiased high-dimensional regression calibration for errors-in-variables log-contrast models
by: Zhao, Huali, et al.
Published: (2024)

VICatMix: variational Bayesian clustering and variable selection for discrete biomedical data
by: Rao, Jackie, et al.
Published: (2024)

PliableBVS: A flexible Bayesian variable selection method for modeling interactions with mandatory modifying variables
by: Asenso, Theophilus Quachie, et al.
Published: (2026)

Semi-supervised Clustering Through Representation Learning of Large-scale EHR Data
by: Wang, Linshanshan, et al.
Published: (2025)

Using Platt's scaling for calibration after undersampling -- limitations and how to address them
by: Phelps, Nathan, et al.
Published: (2024)

A joint optimization approach to identifying sparse dynamics using least squares kernel collocation
by: Hsu, Alexander W., et al.
Published: (2025)

Tuning diagonal scale matrices for HMC
by: Tran, Jimmy Huy, et al.
Published: (2024)

Assumption violations in causal discovery and the robustness of score matching
by: Montagna, Francesco, et al.
Published: (2023)

Double Machine Learning for Conditional Moment Restrictions: IV Regression, Proximal Causal Learning and Beyond
by: Shao, Daqian, et al.
Published: (2025)

Hard and Soft EM in Bayesian Network Learning from Incomplete Data
by: Ruggieri, Andrea, et al.
Published: (2020)

Robust variable selection for spatial point processes observed with noise
by: Sturm, Dominik, et al.
Published: (2025)

Time-to-event prediction for grouped variables using Exclusive Lasso
by: Ravi, Dayasri, et al.
Published: (2025)

Variational empirical Bayes variable selection in high-dimensional logistic regression
by: Tang, Yiqi, et al.
Published: (2025)

Arc travel time and path choice model estimation subsumed
by: Mohammadpour, Sobhan, et al.
Published: (2022)

Markov chain Monte Carlo without evaluating the target: an auxiliary variable approach
by: Yuan, Wei, et al.
Published: (2024)

Self-Compatibility: Evaluating Causal Discovery without Ground Truth
by: Faller, Philipp M., et al.
Published: (2023)

Large-scale entity resolution via microclustering Ewens--Pitman random partitions
by: Beraha, Mario, et al.
Published: (2025)