:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chen, Yinsong, Yu, Samson S., Li, Zhong, Lim, Chee Peng
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2605.21114
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Bayesian Framework for Uncertainty-Aware Explanations in Power Quality Disturbance Classification
by: Chen, Yinsong, et al.
Published: (2026)

Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation
by: Chen, Yinsong, et al.
Published: (2024)

A Posterior-Predictive Variance Decomposition for Epistemic and Aleatoric Uncertainty in Wind Power Forecasting
by: Chen, Yinsong, et al.
Published: (2026)

Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence
by: Mikriukov, Georgii, et al.
Published: (2026)

Uncertainty Quantification as a Principled Foundation for Explainable Artificial Intelligence: A Case Study of Counterfactual Explanations
by: Sokol, Kacper, et al.
Published: (2025)

Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective
by: Xiong, Haoyi, et al.
Published: (2024)

Shaping Initial State Prevents Modality Competition in Multi-modal Fusion: A Two-stage Scheduling Framework via Fast Partial Information Decomposition
by: Tang, Jiaqi, et al.
Published: (2025)

Uncertainty-Aware Explainable Federated Learning
by: Zhang, Yanci, et al.
Published: (2025)

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
by: Salih, Ahmed, et al.
Published: (2023)

Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach
by: Wang, Yinsong, et al.
Published: (2024)

Explainable Artificial Intelligence for Medical Applications: A Review
by: Sun, Qiyang, et al.
Published: (2024)

Robustness of Explainable Artificial Intelligence in Industrial Process Modelling
by: Kantz, Benedikt, et al.
Published: (2024)

RewardUQ: A Unified Framework for Uncertainty-Aware Reward Models
by: Yang, Daniel, et al.
Published: (2026)

Uncertainty-Aware Explainable Recommendation with Large Language Models
by: Peng, Yicui, et al.
Published: (2024)

Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data
by: Wang, Yinsong, et al.
Published: (2026)

TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality
by: Wang, Yinsong, et al.
Published: (2023)

A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning
by: Du, Honglin, et al.
Published: (2026)

Explainable Artificial Intelligence Techniques for Irregular Temporal Classification of Multidrug Resistance Acquisition in Intensive Care Unit Patients
by: Escudero-Arnanz, Óscar, et al.
Published: (2024)

Explainable Artificial Intelligence and Multicollinearity : A Mini Review of Current Approaches
by: Salih, Ahmed M
Published: (2024)

Explainable Artificial Intelligence for Dependent Features: Additive Effects of Collinearity
by: Salih, Ahmed M
Published: (2024)

Explainable Artificial Intelligence for identifying profitability predictors in Financial Statements
by: Piazza, Marco, et al.
Published: (2025)

From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence
by: Wang, Tianyang, et al.
Published: (2025)

ABE: A Unified Framework for Robust and Faithful Attribution-Based Explainability
by: Zhu, Zhiyu, et al.
Published: (2025)

Sparse-PGD: A Unified Framework for Sparse Adversarial Perturbations Generation
by: Zhong, Xuyang, et al.
Published: (2024)

Robust Intrusion Detection System with Explainable Artificial Intelligence
by: Paltun, Betül Güvenç, et al.
Published: (2025)

Concept-Based Explainable Artificial Intelligence: Metrics and Benchmarks
by: Aysel, Halil Ibrahim, et al.
Published: (2025)

Evaluation of Seismic Artificial Intelligence with Uncertainty
by: Myren, Samuel, et al.
Published: (2025)

Stratify: Rethinking Federated Learning for Non-IID Data through Balanced Sampling
by: Wong, Hui Yeok, et al.
Published: (2025)

Explainable Artificial Intelligence (XAI) for Internet of Things: A Survey
by: Kok, Ibrahim, et al.
Published: (2022)

A Hybrid Intelligent Framework for Uncertainty-Aware Condition Monitoring of Industrial Systems
by: Ahang, Maryam, et al.
Published: (2026)

Methods for Class-Imbalanced Learning with Support Vector Machines: A Review and an Empirical Evaluation
by: Rezvani, Salim, et al.
Published: (2024)

A Unified Shape-Aware Foundation Model for Time Series Classification
by: Liu, Zhen, et al.
Published: (2026)

Explainable Artificial Intelligence Techniques for Accurate Fault Detection and Diagnosis: A Review
by: Maged, Ahmed, et al.
Published: (2024)

Visual Analytics for Explainable and Trustworthy Artificial Intelligence
by: Chatzimparmpas, Angelos
Published: (2025)

Explainable Artificial Intelligence in Biomedical Image Analysis: A Comprehensive Survey
by: Dagnaw, Getamesay Haile, et al.
Published: (2025)

Latent Distribution Decoupling: A Probabilistic Framework for Uncertainty-Aware Multimodal Emotion Recognition
by: Huang, Jingwang, et al.
Published: (2025)

Uncertainty Quantification of Wind Gust Predictions in the Northeast United States: An Evidential Neural Network and Explainable Artificial Intelligence Approach
by: Jahan, Israt, et al.
Published: (2025)

A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligence
by: Pagliari, Roberto, et al.
Published: (2024)

Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks
by: Vadillo, Jon, et al.
Published: (2024)

Uncertainty-Aware Fairness-Adaptive Classification Trees
by: Gottard, Anna, et al.
Published: (2024)