Cover Image

Multi-View Contrastive Learning for Robust Domain Adaptation in Medical Time Series Analysis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Oh, YongKyung, Bui, Alex
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification
by: Oh, YongKyung, et al.
Published: (2025)

DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series Analysis
by: Oh, YongKyung, et al.
Published: (2024)

Comprehensive Review of Neural Differential Equations for Time Series Analysis
by: Oh, YongKyung, et al.
Published: (2025)

FlowPath: Learning Data-Driven Manifolds with Invertible Flows for Robust Irregularly-sampled Time Series Classification
by: Oh, YongKyung, et al.
Published: (2025)

Position: State-of-the-Art Claims Require State-of-the-Art Evidence
by: Oh, YongKyung
Published: (2026)

Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
by: Oh, YongKyung, et al.
Published: (2024)

DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series
by: Darban, Zahra Zamanzadeh, et al.
Published: (2024)

Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review
by: Oh, YongKyung, et al.
Published: (2026)

LEAVES: Learning Views for Time-Series Biobehavioral Data in Contrastive Learning
by: Yu, Han, et al.
Published: (2022)

Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations
by: Oh, YongKyung, et al.
Published: (2025)

TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
by: Huang, Yu-Hao, et al.
Published: (2025)

Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates
by: Yu, Chengqing, et al.
Published: (2025)

Time and Frequency Synergy for Source-Free Time-Series Domain Adaptations
by: Furqon, Muhammad Tanzil, et al.
Published: (2024)

Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly Detection
by: Kim, HyunGi, et al.
Published: (2025)

Soft Contrastive Learning for Time Series
by: Lee, Seunghan, et al.
Published: (2023)

Augmented Contrastive Clustering with Uncertainty-Aware Prototyping for Time Series Test Time Adaptation
by: Gong, Peiliang, et al.
Published: (2025)

Deep Unsupervised Domain Adaptation for Time Series Classification: a Benchmark
by: Fawaz, Hassan Ismail, et al.
Published: (2023)

TSI: A Multi-View Representation Learning Approach for Time Series Forecasting
by: Gao, Wentao, et al.
Published: (2024)

Bridging Contrastive Learning and Domain Adaptation: Theoretical Perspective and Practical Application
by: Quintana, Gonzalo Iñaki, et al.
Published: (2025)

Tensor-Fused Multi-View Graph Contrastive Learning
by: Wu, Yujia, et al.
Published: (2024)

Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation
by: Kim, Seonghwi, et al.
Published: (2026)

Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation
by: Ragab, Mohamed, et al.
Published: (2024)

TopoCL: Topological Contrastive Learning for Time Series
by: Kim, Namwoo, et al.
Published: (2025)

Denoising-Aware Contrastive Learning for Noisy Time Series
by: Zhou, Shuang, et al.
Published: (2024)

Time Series Domain Adaptation via Latent Invariant Causal Mechanism
by: Cai, Ruichu, et al.
Published: (2025)

Black-Box Time-Series Domain Adaptation via Cross-Prompt Foundation Models
by: Furqon, M. T., et al.
Published: (2025)

From Entanglement to Alignment: Representation Space Decomposition for Unsupervised Time Series Domain Adaptation
by: Cai, Rongyao, et al.
Published: (2025)

Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection
by: Chen, Feiyi, et al.
Published: (2023)

Weighted Contrastive Learning for Anomaly-Aware Time-Series Forecasting
by: Ekstrand, Joel, et al.
Published: (2025)

Time Series Representation Learning with Supervised Contrastive Temporal Transformer
by: Liu, Yuansan, et al.
Published: (2024)

Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification
by: Liu, Ziyu, et al.
Published: (2024)

In-Context Policy Adaptation via Cross-Domain Skill Diffusion
by: Yoo, Minjong, et al.
Published: (2025)

Contrastive Time Series Forecasting with Anomalies
by: Ekstrand, Joel, et al.
Published: (2025)

MEET-Sepsis: Multi-Endogenous-View Enhanced Time-Series Representation Learning for Early Sepsis Prediction
by: Tan, Zexi, et al.
Published: (2025)

MedGNN: Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification
by: Fan, Wei, et al.
Published: (2025)

Unsupervised Contrastive Learning for Robust RF Device Fingerprinting Under Time-Domain Shift
by: Chen, Jun, et al.
Published: (2024)

Repetitive Contrastive Learning Enhances Mamba's Selectivity in Time Series Prediction
by: Yan, Wenbo, et al.
Published: (2025)

Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning
by: Gao, Haozhi, et al.
Published: (2024)

Time-Series Contrastive Learning against False Negatives and Class Imbalance
by: Jin, Xiyuan, et al.
Published: (2023)

Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection
by: Chen, Katrina, et al.
Published: (2023)