Cover Image

Reliable data clustering with Bayesian community detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Neuman, Magnus, Smiljanić, Jelena, Rosvall, Martin
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Data Analysis, Statistics and Probability Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Community Detection with the Map Equation and Infomap: Theory and Applications
by: Smiljanić, Jelena, et al.
Published: (2023)

Bayesian Hierarchical Models and the Maximum Entropy Principle
by: Brewer, Brendon J.
Published: (2026)

Learning dynamical systems with hit-and-run random feature maps
by: Mandal, Pinak, et al.
Published: (2025)

On the choice of the non-trainable internal weights in random feature maps
by: Mandal, Pinak, et al.
Published: (2024)

Towards Continuous-time Causal Foundation Models
by: Thumm, Dennis, et al.
Published: (2026)

Linear scaling causal discovery from high-dimensional time series by dynamical community detection
by: Allione, Matteo, et al.
Published: (2025)

Hierarchical topological clustering
by: Carpio, Ana, et al.
Published: (2025)

Practically Effective Adjustment Variable Selection in Causal Inference
by: Noda, Atsushi, et al.
Published: (2025)

Forecasting with an N-dimensional Langevin Equation and a Neural-Ordinary Differential Equation
by: Malpica-Morales, Antonio, et al.
Published: (2024)

Non-parametric finite-sample credible intervals with one-dimensional priors: a middle ground between Bayesian and frequentist intervals
by: Ritmeester, Tim
Published: (2026)

Quantifying uncertainty in the numerical integration of evolution equations based on Bayesian isotonic regression
by: Miyatake, Yuto, et al.
Published: (2024)

Multivariate extensions of the Multilevel Best Linear Unbiased Estimator for ensemble-variational data assimilation
by: Destouches, Mayeul, et al.
Published: (2023)

Statistical limits of correlation detection in trees
by: Ganassali, Luca, et al.
Published: (2022)

A low-rank ensemble Kalman filter for elliptic observations
by: Provost, Mathieu Le, et al.
Published: (2022)

Reliable Statistical Guarantees for Conformal Predictors with Small Datasets
by: Sánchez-Domínguez, Miguel, et al.
Published: (2025)

Bayesian hypergraph inference from scarce and noisy dynamical observations
by: Tang, Katerina, et al.
Published: (2026)

Identifiability and improper solutions in the probabilistic partial least squares regression with unique variance
by: Arai, Takashi
Published: (2025)

Testing of tempered fractional Brownian motions
by: Macioszek, Katarzyna, et al.
Published: (2025)

Identifiable factor analysis for mixed continuous and binary variables based on the Gaussian-Grassmann distribution
by: Arai, Takashi
Published: (2025)

Identifying Intended Effects with Causal Models
by: Compagno, Dario
Published: (2024)

Evaluating the Uncertainty in Mean Residual Times: Estimators Based on Residence Times from Discrete Time Processes
by: Sánchez, Hernán R., et al.
Published: (2024)

Disentangling high order effects in the transfer entropy
by: Stramaglia, Sebastiano, et al.
Published: (2024)

Variational Dimension Lifting for Robust Tracking of Nonlinear Stochastic Dynamics
by: Ashenafi, Yonatan L.
Published: (2026)

Local statistical moments to capture Kramers-Moyal coefficients
by: Wiedemann, Christian, et al.
Published: (2024)

Thermodynamically rational decision making under uncertainty
by: Daimer, Dorian, et al.
Published: (2023)

Dissecting Spectral Granger Causality through Partial Information Decomposition
by: Faes, Luca, et al.
Published: (2026)

Preserving linear invariants in ensemble filtering methods
by: Provost, Mathieu Le, et al.
Published: (2024)

Particle Filtering for Non-Deterministic Electrocardiographic Imaging
by: Lagracie, Emma, et al.
Published: (2025)

A feature-based information-theoretic approach for detecting interpretable, long-timescale pairwise interactions from time series
by: Nguyen, Aria, et al.
Published: (2024)

Machine learning approach to detect dynamical states from recurrence measures
by: Thakur, Dheeraja, et al.
Published: (2024)

Active Learning with Fully Bayesian Neural Networks for Discontinuous and Nonstationary Data
by: Ziatdinov, Maxim
Published: (2024)

Least Squares as Random Walks
by: Kostinski, Alexander, et al.
Published: (2025)

An information field theory approach to Bayesian state and parameter estimation in dynamical systems
by: Hao, Kairui, et al.
Published: (2023)

On the statistical analysis of grouped data: when Pearson $χ^2$ and other divisible statistics are not goodness-of-fit tests
by: Algeri, Sara, et al.
Published: (2024)

Testing maximum entropy models with e-values
by: Giuffrida, Francesca, et al.
Published: (2025)

A statistical mechanics approach to de-biasing and uncertainty estimation in LASSO for random measurements
by: Takahashi, Takashi, et al.
Published: (2018)

Tunable correlation retention: A statistical method for generating synthetic data
by: Jävergård, Nicklas, et al.
Published: (2024)

Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guides
by: Karumuri, Sharmila, et al.
Published: (2023)

Covering Unknown Correlations in Bayesian Priors by Inflating Uncertainties
by: Koch, Lukas
Published: (2025)

Bayesian symbolic regression: Automated equation discovery from a physicists' perspective
by: Guimera, Roger, et al.
Published: (2025)