:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Mohammadi, Arman, Krysander, Mattias, Jung, Daniel, Frisk, Erik
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2509.18810
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

The LiU-ICE Benchmark -- An Industrial Fault Diagnosis Case Study
di: Jung, Daniel, et al.
Pubblicazione: (2024)

Neural Network-Based Piecewise Survival Models
di: Holmer, Olov, et al.
Pubblicazione: (2024)

Usage-Specific Survival Modeling Based on Operational Data and Neural Networks
di: Holmer, Olov, et al.
Pubblicazione: (2024)

Stability-Informed Initialization of Neural Ordinary Differential Equations
di: Westny, Theodor, et al.
Pubblicazione: (2023)

Diffusion-Based Environment-Aware Trajectory Prediction
di: Westny, Theodor, et al.
Pubblicazione: (2024)

UBMF: Uncertainty-Aware Bayesian Meta-Learning Framework for Fault Diagnosis with Imbalanced Industrial Data
di: Lian, Zhixuan, et al.
Pubblicazione: (2025)

AI-Powered Machine Learning Approaches for Fault Diagnosis in Industrial Pumps
di: Alghtus, Khaled M. A., et al.
Pubblicazione: (2025)

Probabilistic Consistency in Machine Learning and Its Connection to Uncertainty Quantification
di: Patrone, Paul, et al.
Pubblicazione: (2025)

Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics
di: Frauenknecht, Bernd, et al.
Pubblicazione: (2026)

Uncertainty Quantification in Probabilistic Machine Learning Models: Theory, Methods, and Insights
di: Ajirak, Marzieh, et al.
Pubblicazione: (2025)

Uncertainty-Aware Diagnostics for Physics-Informed Machine Learning
di: Daniels, Mara, et al.
Pubblicazione: (2025)

An Uncertainty-Aware ED-LSTM for Probabilistic Suffix Prediction
di: Mustroph, Henryk, et al.
Pubblicazione: (2025)

Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning
di: Pourkamali-Anaraki, Farhad, et al.
Pubblicazione: (2024)

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

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

Operationalization of Machine Learning with Serverless Architecture: An Industrial Operationalization of Machine Learning with Serverless Architecture: An Industrial Implementation for Harmonized System Code Prediction
di: Kandappareddigari, Sai Vineeth, et al.
Pubblicazione: (2026)

UAMDP: Uncertainty-Aware Markov Decision Process for Risk-Constrained Reinforcement Learning from Probabilistic Forecasts
di: Koren, Michal, et al.
Pubblicazione: (2025)

The Probabilistic Tsetlin Machine: A Novel Approach to Uncertainty Quantification
di: Abeyrathna, K. Darshana, et al.
Pubblicazione: (2024)

Comparison of Deterministic and Probabilistic Machine Learning Algorithms for Precise Dimensional Control and Uncertainty Quantification in Additive Manufacturing
di: Sanpui, Dipayan, et al.
Pubblicazione: (2025)

Navigating Uncertainties in Machine Learning for Structural Dynamics: A Comprehensive Survey of Probabilistic and Non-Probabilistic Approaches in Forward and Inverse Problems
di: Yan, Wang-Ji, et al.
Pubblicazione: (2024)

Uncertainty in Machine Learning
di: Weytjens, Hans, et al.
Pubblicazione: (2025)

UPLME: Uncertainty-Aware Probabilistic Language Modelling for Robust Empathy Regression
di: Hasan, Md Rakibul, et al.
Pubblicazione: (2025)

A Trustworthy Industrial Fault Diagnosis Architecture Integrating Probabilistic Models and Large Language Models
di: wu, Yue
Pubblicazione: (2025)

Explainable AI to Improve Machine Learning Reliability for Industrial Cyber-Physical Systems
di: Jutte, Annemarie, et al.
Pubblicazione: (2026)

Probabilistic Scoring Lists for Interpretable Machine Learning
di: Hanselle, Jonas, et al.
Pubblicazione: (2024)

Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits
di: Sidheekh, Sahil, et al.
Pubblicazione: (2024)

Uncertainty-Aware PPG-2-ECG for Enhanced Cardiovascular Diagnosis using Diffusion Models
di: Belhasin, Omer, et al.
Pubblicazione: (2024)

Machine Learning Infused Distributed Optimization for Coordinating Virtual Power Plant Assets
di: Li, Meiyi, et al.
Pubblicazione: (2023)

Probabilistic Super-Resolution for High-Fidelity Physical System Simulations with Uncertainty Quantification
di: Zhang, Pengyu, et al.
Pubblicazione: (2025)

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

Uncertainty-Aware Graph Structure Learning
di: Han, Shen, et al.
Pubblicazione: (2025)

Tractable Sharpness-Aware Learning of Probabilistic Circuits
di: Suresh, Hrithik, et al.
Pubblicazione: (2025)

Efficient Reinforcement Learning in Probabilistic Reward Machines
di: Lin, Xiaofeng, et al.
Pubblicazione: (2024)

A Review of Machine Learning Techniques in Imbalanced Data and Future Trends
di: Jafarigol, Elaheh, et al.
Pubblicazione: (2023)

Calibrated Value-Aware Model Learning with Probabilistic Environment Models
di: Voelcker, Claas, et al.
Pubblicazione: (2025)

LUCID: Learning-Enabled Uncertainty-Aware Certification of Stochastic Dynamical Systems
di: Casablanca, Ernesto, et al.
Pubblicazione: (2025)

Uncertainty-Aware Robust Learning on Noisy Graphs
di: Chen, Shuyi, et al.
Pubblicazione: (2023)

Learning Uncertainty-Aware Temporally-Extended Actions
di: Lee, Joongkyu, et al.
Pubblicazione: (2024)

Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models
di: Löfström, Tuwe, et al.
Pubblicazione: (2024)

Heterogeneity-Aware Personalized Federated Learning for Industrial Predictive Analytics
di: Hu, Yuhan, et al.
Pubblicazione: (2026)