Image de couverture de livre

DeepFMEA -- A Scalable Framework Harmonizing Process Expertise and Data-Driven PHM

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Netsch, Christoph, Schöpe, Till, Schindele, Benedikt, Jayakumar, Joyam
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Machine Learning Approaches for Diagnostics and Prognostics of Industrial Systems Using Open Source Data from PHM Data Challenges: A Review
par: Su, Hanqi, et autres
Publié: (2023)

Picid: A Modular Evaluation Infrastructure for Reproducible PHM Across Tasks and Domains
par: Telyatnikov, Lev, et autres
Publié: (2026)

A Framework for Streaming Event-Log Prediction in Business Processes
par: Bollig, Benedikt, et autres
Publié: (2024)

A Scalable Curiosity-Driven Game-Theoretic Framework for Long-Tail Multi-Label Learning in Data Mining
par: Yang, Jing, et autres
Publié: (2026)

DeepACTIF: Efficient Feature Attribution via Activation Traces in Neural Sequence Models
par: Hosp, Benedikt W.
Publié: (2025)

OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling
par: Lu, Hongliang, et autres
Publié: (2025)

Inverse Reinforcement Learning by Estimating Expertise of Demonstrators
par: Beliaev, Mark, et autres
Publié: (2024)

Data-Driven Online Model Selection With Regret Guarantees
par: Pacchiano, Aldo, et autres
Publié: (2023)

An Intelligent Fault Diagnosis Method for General Aviation Aircraft Based on Multi-Fidelity Digital Twin and FMEA Knowledge Enhancement
par: Wei, Zhihuan, et autres
Publié: (2026)

DeepFilter: A Transformer-style Framework for Accurate and Efficient Process Monitoring
par: Wang, Hao, et autres
Publié: (2025)

Attention-Driven Multi-Agent Reinforcement Learning: Enhancing Decisions with Expertise-Informed Tasks
par: Kuroswiski, Andre R, et autres
Publié: (2024)

Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training
par: Ye, Chenlu, et autres
Publié: (2025)

Standardizing Your Training Process for Human Activity Recognition Models: A Comprehensive Review in the Tunable Factors
par: Huang, Yiran, et autres
Publié: (2024)

Machine and Deep Learning for Indoor UWB Jammer Localization
par: Fard, Hamed, et autres
Publié: (2025)

A Unified Framework for Locality in Scalable MARL
par: Chakraborty, Sourav, et autres
Publié: (2026)

Reinfier and Reintrainer: Verification and Interpretation-Driven Safe Deep Reinforcement Learning Frameworks
par: Yang, Zixuan, et autres
Publié: (2024)

Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting
par: Nochumsohn, Liran, et autres
Publié: (2024)

TranDRL: A Transformer-Driven Deep Reinforcement Learning Enabled Prescriptive Maintenance Framework
par: Zhao, Yang, et autres
Publié: (2023)

Defining Expertise: Applications to Treatment Effect Estimation
par: Hüyük, Alihan, et autres
Publié: (2024)

Context Neural Networks: A Scalable Multivariate Model for Time Series Forecasting
par: Sriramulu, Abishek, et autres
Publié: (2024)

Deep-and-Wide Learning: Enhancing Data-Driven Inference via Synergistic Learning of Inter- and Intra-Data Representations
par: Islam, Md Tauhidul, et autres
Publié: (2025)

Enabling High Data Throughput Reinforcement Learning on GPUs: A Domain Agnostic Framework for Data-Driven Scientific Research
par: Lan, Tian, et autres
Publié: (2024)

Principled Approximation Methods for Efficient and Scalable Deep Learning
par: Savarese, Pedro
Publié: (2025)

Balancing Fairness, Privacy, and Accuracy: A Multitask Adversarial Framework for Centralized Data-Driven Systems
par: Ekanayake, Imesh, et autres
Publié: (2026)

REFORMER: A ChatGPT-Driven Data Synthesis Framework Elevating Text-to-SQL Models
par: Liu, Shenyang, et autres
Publié: (2025)

A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation
par: Song, Yu, et autres
Publié: (2025)

A General Anchor-Based Framework for Scalable Fair Clustering
par: Wei, Shengfei, et autres
Publié: (2025)

TabSeq: A Framework for Deep Learning on Tabular Data via Sequential Ordering
par: Habib, Al Zadid Sultan Bin, et autres
Publié: (2024)

An Innovative Data-Driven and Adaptive Reinforcement Learning Approach for Context-Aware Prescriptive Process Monitoring
par: Abbasi, Mostafa, et autres
Publié: (2025)

SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes
par: Xiong, Xuyuan, et autres
Publié: (2025)

Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach
par: Mirzaei, Erfan, et autres
Publié: (2026)

Human Expertise in Algorithmic Prediction
par: Alur, Rohan, et autres
Publié: (2024)

Enhancing Obsolescence Forecasting with Deep Generative Data Augmentation: A Semi-Supervised Framework for Low-Data Industrial Applications
par: Saad, Elie, et autres
Publié: (2025)

Can Large Language Models Learn Formal Logic? A Data-Driven Training and Evaluation Framework
par: Xia, Yuan, et autres
Publié: (2025)

Learning Generalized Policies for Fully Observable Non-Deterministic Planning Domains
par: Hofmann, Till, et autres
Publié: (2024)

Scalable and Efficient Methods for Uncertainty Estimation and Reduction in Deep Learning
par: Ahmed, Soyed Tuhin
Publié: (2024)

DeepGate3: Towards Scalable Circuit Representation Learning
par: Shi, Zhengyuan, et autres
Publié: (2024)

A Scalable and Transferable Time Series Prediction Framework for Demand Forecasting
par: Park, Young-Jin, et autres
Publié: (2024)

Ethical and Scalable Automation: A Governance and Compliance Framework for Business Applications
par: Lin, Haocheng
Publié: (2024)

CogScale: Scalable Benchmark for Sequence Processing
par: Bendi-Ouis, Yannis, et autres
Publié: (2026)