Cover Image

A Survey and Comparative Evaluation of Intrinsic Dimension Estimators under the Manifold Hypothesis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bi, Zelong, de Micheaux, Pierre Lafaye
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Manifold Dimension Estimation via Local Graph Structure
by: Bi, Zelong, et al.
Published: (2025)

Generative Flexible Latent Structure Regression (GFLSR) model
by: Grazian, Clara, et al.
Published: (2025)

tBayes-MICE: A Bayesian Approach to Multiple Imputation for Time Series Data
by: Ibenegbu, Amuche, et al.
Published: (2026)

Deep-testing: the case of dependence detection
by: Geenens, Gery, et al.
Published: (2026)

Adaptive Heavy-Tailed Stochastic Gradient Descent
by: Gong, Bodu, et al.
Published: (2025)

A Machine Learning Framework for Handling Unreliable Absence Label and Class Imbalance for Marine Stinger Beaching Prediction
by: Ibenegbu, Amuche, et al.
Published: (2025)

Intrinsic Bayesian Cramér-Rao Bound with an Application to Covariance Matrix Estimation
by: Bouchard, Florent, et al.
Published: (2023)

Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data
by: Zeng, Cheng, et al.
Published: (2025)

Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations
by: Murph, Alexander C., et al.
Published: (2023)

High-Dimensional Statistical Process Control via Manifold Fitting and Learning
by: Tas, Burak I., et al.
Published: (2025)

Double Machine Learning Methods for Estimating Average Treatment Effects: A Comparative Study
by: Tan, Xiaoqing, et al.
Published: (2022)

Mapping Methane -- The Impact of Dairy Farm Practices on Emissions Through Satellite Data and Machine Learning
by: Bi, Hanqing, et al.
Published: (2024)

A linear regression model for quantile function data applied to paired pulmonary 3d CT scans
by: Béclin, Marie-Félicia, et al.
Published: (2024)

Inductive Global and Local Manifold Approximation and Projection
by: Kim, Jungeum, et al.
Published: (2024)

Flow Battery Manifold Design with Heterogeneous Inputs Through Generative Adversarial Neural Networks
by: Seng, Eric, et al.
Published: (2025)

Design a Metric Robust to Complicated High Dimensional Noise for Efficient Manifold Denoising
by: Wu, Hau-Tieng
Published: (2024)

Local Intrinsic Dimensionality of Ground Motion Data for Early Detection of Complex Catastrophic Slope Failure
by: Liu, Yuansan, et al.
Published: (2026)

E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing
by: Sadhuka, Shuvom, et al.
Published: (2025)

Statistical Reinforcement Learning in the Real World: A Survey of Challenges and Future Directions
by: Gazi, Asim H., et al.
Published: (2026)

Data is missing again -- Reconstruction of power generation data using $k$-Nearest Neighbors and spectral graph theory
by: Pierrot, Amandine, et al.
Published: (2024)

The Partial Testimony of Logs: Evaluation of Language Model Generation under Confounded Model Choice
by: Jin, Jikai, et al.
Published: (2026)

A Framework for Scalable Ambient Air Pollution Concentration Estimation
by: Berrisford, Liam J, et al.
Published: (2024)

Sustainable Greenhouse Microclimate Modeling: A Comparative Analysis of Recurrent and Graph Neural Networks
by: Seri, Emiliano, et al.
Published: (2025)

Model-Agnostic Interpretation Framework in Machine Learning: A Comparative Study in NBA Sports
by: Liu, Shun
Published: (2024)

A Metric-based Principal Curve Approach for Learning One-dimensional Manifold
by: Cuicizion, Eliuvish
Published: (2024)

Which Imputation Fits Which Feature Selection Method? A Survey-Based Simulation Study
by: Schwerter, Jakob, et al.
Published: (2024)

Optimal Transport for Treatment Effect Estimation
by: Wang, Hao, et al.
Published: (2023)

Communication-Efficient Distributed Estimation and Inference for Cox's Model
by: Bayle, Pierre, et al.
Published: (2023)

Common Structure Discovery in Collections of Bipartite Networks: Application to Pollination Systems
by: Lacoste, Louis, et al.
Published: (2025)

Advancing Causal Inference: A Nonparametric Approach to ATE and CATE Estimation with Continuous Treatments
by: Souto, Hugo Gobato, et al.
Published: (2024)

Do we actually understand the impact of renewables on electricity prices? A causal inference approach
by: Cacciarelli, Davide, et al.
Published: (2025)

Gini Score under Ties and Case Weights
by: Brauer, Alexej, et al.
Published: (2025)

A Bayesian Regression Approach for Estimating the Impact of COVID-19 on Consumer Behavior in the Restaurant Industry
by: Hinduja, H., et al.
Published: (2024)

Modeling Parkinson's Disease Progression Using Longitudinal Voice Biomarkers: A Comparative Study of Statistical and Neural Mixed-Effects Models
by: Tong, Ran, et al.
Published: (2025)

A Statistical Framework for Spatial Boundary Estimation and Change Detection: Application to the Sahel Sahara Climate Transition
by: Tivenan, Stephen, et al.
Published: (2025)

Federated Item Response Models: A Gradient-driven Privacy-preserving Framework for Distributed Psychometric Estimation
by: Zhou, Biying, et al.
Published: (2025)

Clustering Approaches for Mixed-Type Data: A Comparative Study
by: Ghattas, Badih, et al.
Published: (2025)

Bayesian Estimation of Extreme Quantiles and the Exceedance Distribution for Paretian Tails
by: Johnston, Douglas E.
Published: (2025)

Variational Approximated Restricted Maximum Likelihood Estimation for Spatial Data
by: Thakur, Debjoy
Published: (2026)

Predictive Uncertainty in Short-Term PV Forecasting under Missing Data: A Multiple Imputation Approach
by: Pashmchi, Parastoo, et al.
Published: (2026)