Cover Image

Supervised Contrastive Learning based Dual-Mixer Model for Remaining Useful Life Prediction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fu, En, Hu, Yanyan, Peng, Kaixiang, Chu, Yuxin
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PEFT-MuTS: A Multivariate Parameter-Efficient Fine-Tuning Framework for Remaining Useful Life Prediction based on Cross-domain Time Series Representation Model
by: Fu, En, et al.
Published: (2026)

IIP-Mixer:Intra-Inter Patch Mixing Architecture for Battery Remaining Useful Life Prediction
by: Ye, Guangzai, et al.
Published: (2024)

Automated Machine Learning for Remaining Useful Life Predictions
by: Zöller, Marc-André, et al.
Published: (2023)

A Multi-Granularity Supervised Contrastive Framework for Remaining Useful Life Prediction of Aero-engines
by: He, Zixuan, et al.
Published: (2024)

Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning
by: Fu, En, et al.
Published: (2024)

Mixup Domain Adaptations for Dynamic Remaining Useful Life Predictions
by: Furqon, Muhammad Tanzil, et al.
Published: (2024)

Meta-Learning and Knowledge Discovery based Physics-Informed Neural Network for Remaining Useful Life Prediction
by: Wang, Yu, et al.
Published: (2025)

Multiscale Dual-path Feature Aggregation Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
by: Lv, Zihao, et al.
Published: (2025)

Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation
by: Hou, Yubo, et al.
Published: (2026)

CNN-LSTM Hybrid Deep Learning Model for Remaining Useful Life Estimation
by: G, Muthukumar, et al.
Published: (2024)

Uncertainty-Aware Deep Learning Framework for Remaining Useful Life Prediction in Turbofan Engines with Learned Aleatoric Uncertainty
by: Sharma, Krishang
Published: (2025)

Survival Analysis with Machine Learning for Predicting Li-ion Battery Remaining Useful Life
by: Xue, Jingyuan, et al.
Published: (2025)

Fed-Joint: Joint Modeling of Nonlinear Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning
by: Jeong, Cheoljoon, et al.
Published: (2025)

HyBattNet: Hybrid Framework for Predicting the Remaining Useful Life of Lithium-Ion Batteries
by: Tran, Khoa, et al.
Published: (2025)

A Quantile Regression Approach for Remaining Useful Life Estimation with State Space Models
by: Frizzo, Davide, et al.
Published: (2025)

A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
by: Wang, Yucheng, et al.
Published: (2024)

Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
by: Wang, Yucheng, et al.
Published: (2025)

BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction
by: Zhang, Zekai, et al.
Published: (2025)

FTT-GRU: A Hybrid Fast Temporal Transformer with GRU for Remaining Useful Life Prediction
by: Chirukiri, Varun Teja, et al.
Published: (2025)

A Novel Preprocessing-Driven Approach to Remaining Useful Life (RUL) Prediction Using Temporal Convolutional Networks (TCN)
by: Imbert, Florent, et al.
Published: (2026)

A Multi-Task Targeted Learning Framework for Lithium-Ion Battery State-of-Health and Remaining Useful Life
by: Wang, Chenhan, et al.
Published: (2026)

Remaining Useful Life Prediction for Batteries Utilizing an Explainable AI Approach with a Predictive Application for Decision-Making
by: Paneru, Biplov, et al.
Published: (2024)

Remaining Useful Life Prediction: A Study on Multidimensional Industrial Signal Processing and Efficient Transfer Learning Based on Large Language Models
by: Chen, Yan, et al.
Published: (2024)

A Novel Multimodal RUL Framework for Remaining Useful Life Estimation with Layer-wise Explanations
by: Razzaq, Waleed, et al.
Published: (2025)

Hybrid Gaussian Process Regression with Temporal Feature Extraction for Partially Interpretable Remaining Useful Life Interval Prediction in Aeroengine Prognostics
by: Niu, Tian, et al.
Published: (2024)

Turbofan Engine Remaining Useful Life (RUL) Prediction Based on Bi-Directional Long Short-Term Memory (BLSTM)
by: Sherifi, Abedin
Published: (2024)

Scientific Machine Learning for Engine Health Management and Remaining Useful Life Prediction
by: Barry-Straume, Jostein, et al.
Published: (2026)

A Change Point Detection Integrated Remaining Useful Life Estimation Model under Variable Operating Conditions
by: Arunan, Anushiya, et al.
Published: (2024)

Dual Perspectives on Non-Contrastive Self-Supervised Learning
by: Ponce, Jean, et al.
Published: (2025)

Learning Label Hierarchy with Supervised Contrastive Learning
by: Lian, Ruixue, et al.
Published: (2024)

SDMixer: Sparse Dual-Mixer for Time Series Forecasting
by: Ao, Xiang
Published: (2026)

Sparse Low-Ranked Self-Attention Transformer for Remaining Useful Lifetime Prediction of Optical Fiber Amplifiers
by: Schneider, Dominic, et al.
Published: (2024)

TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
by: Wang, Shiyu, et al.
Published: (2024)

Are Foundation Models Useful for Bankruptcy Prediction?
by: Kostrzewa, Marcin, et al.
Published: (2025)

Self-Reinforced Graph Contrastive Learning
by: Hsieh, Chou-Ying, et al.
Published: (2025)

Uncertainty-Aware Metabolic Stability Prediction with Dual-View Contrastive Learning
by: Guo, Peijin, et al.
Published: (2025)

Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis
by: Dai, Yajiao, et al.
Published: (2025)

Rethinking Remaining Useful Life Prediction with Scarce Time Series Data: Regression under Indirect Supervision
by: Cheng, Jiaxiang, et al.
Published: (2025)

DPWMixer: Dual-Path Wavelet Mixer for Long-Term Time Series Forecasting
by: Qianyang, Li, et al.
Published: (2025)

Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
by: Jian, Xiangru, et al.
Published: (2024)