Cover Image

Robust variable selection for spatial point processes observed with noise

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sturm, Dominik, Sbalzarini, Ivo F.
Format:	Preprint
Published:	2025
Subjects:	Methodology Machine Learning Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Statistical inference after variable selection in Cox models: A simulation study
by: Schemet, Lena, et al.
Published: (2026)

Numerically robust Gaussian state estimation with singular observation noise
by: Krämer, Nicholas, et al.
Published: (2025)

Modeling nonstationary spatial processes with normalizing flows
by: Nag, Pratik, et al.
Published: (2025)

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

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

Beyond Differences: Doubly Robust Meta-Learners for Ratio-Based Treatment Effects
by: Fuchs, Michael, et al.
Published: (2026)

Principal component analysis balancing prediction and approximation accuracy for spatial data
by: Cheng, Si, et al.
Published: (2024)

A self-supervised learning approach for denoising autoregressive models with additive noise: finite and infinite variance cases
by: Banerjee, Sayantan, 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)

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

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

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

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

Dirichlet process mixtures of block $g$ priors for model selection and prediction in linear models
by: Porwal, Anupreet, et al.
Published: (2024)

Gaussian process interpolation with conformal prediction: methods and comparative analysis
by: Pion, Aurélien, et al.
Published: (2024)

Robust and Conjugate Spatio-Temporal Gaussian Processes
by: Laplante, William, et al.
Published: (2025)

pared: Model selection using multi-objective optimization
by: Das, Priyam, et al.
Published: (2025)

Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
by: Li, Chengkun, et al.
Published: (2023)

Preconditioned Robust Neural Posterior Estimation for Misspecified Simulators
by: Kelly, Ryan P., et al.
Published: (2026)

Robust Tensor Regression with Nonconvexity: Algorithmic and Statistical Theory
by: Song, Zihao, et al.
Published: (2026)

Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
by: Petit, Sébastien, et al.
Published: (2022)

Robust Matrix Completion for Discrete Rating-Scale Data: Coping with Fake Profiles in Recommender Systems
by: Archimbaud, Aurore, et al.
Published: (2024)

Multiply-Robust Causal Change Attribution
by: Quintas-Martinez, Victor, et al.
Published: (2024)

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

Cross-validation for change-point regression: pitfalls and solutions
by: Pein, Florian, et al.
Published: (2021)

Causality-oriented robustness: exploiting general noise interventions
by: Shen, Xinwei, et al.
Published: (2023)

Robustly estimating heterogeneity in factorial data using Rashomon Partitions
by: Venkateswaran, Aparajithan, et al.
Published: (2024)

Root Cause Analysis of Outliers in Unknown Cyclic Graphs
by: Schkoda, Daniela, et al.
Published: (2025)

Chemical Reaction Networks Learn Better than Spiking Neural Networks
by: Jaffard, Sophie, et al.
Published: (2026)

Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression
by: Dandapanthula, Sanjit, et al.
Published: (2026)

Integrated path stability selection
by: Melikechi, Omar, et al.
Published: (2024)

Bayesian Cox model with graph-structured variable selection priors for multi-omics biomarker identification
by: Hermansen, Tobias Østmo, et al.
Published: (2025)

The MELODIC family for simultaneous binary logistic regression in a reduced space
by: de Rooij, Mark, et al.
Published: (2021)

Multiple Linked Tensor Factorization
by: Kang, Zhiyu, et al.
Published: (2025)

A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC
by: Llorente, F., et al.
Published: (2021)

ACS: An interactive framework for conformal selection
by: Gui, Yu, et al.
Published: (2025)

A note on the area under the likelihood and the fake evidence for model selection
by: Martino, L., et al.
Published: (2026)

Maximin Robust Bayesian Experimental Design
by: Abdulsamad, Hany, et al.
Published: (2026)

Assessing the overall and partial causal well-specification of nonlinear additive noise models
by: Schultheiss, Christoph, et al.
Published: (2023)