Cover Image

Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fu, En, Hu, Yanyan
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)

Supervised Contrastive Learning based Dual-Mixer Model for Remaining Useful Life Prediction
by: Fu, En, et al.
Published: (2024)

T-Rep: Representation Learning for Time Series using Time-Embeddings
by: Fraikin, Archibald, et al.
Published: (2023)

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

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

TIFO: Time-Invariant Frequency Operator for Stationarity-Aware Representation Learning in Time Series
by: Piao, Xihao, et al.
Published: (2026)

Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting
by: Fan, Wei, et al.
Published: (2024)

MobiCLR: Mobility Time Series Contrastive Learning for Urban Region Representations
by: Kim, Namwoo, et al.
Published: (2025)

UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
by: Feng, Shikun, et al.
Published: (2024)

Myna: Masking-Based Contrastive Learning of Musical Representations
by: Yonay, Ori, et al.
Published: (2025)

AudioMosaic: Contrastive Masked Audio Representation Learning
by: Huang, Hanxun, et al.
Published: (2026)

TimeDRL: Disentangled Representation Learning for Multivariate Time-Series
by: Chang, Ching, et al.
Published: (2023)

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

Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
by: Zhao, Lifan, et al.
Published: (2024)

Scalable Numerical Embeddings for Multivariate Time Series: Enhancing Healthcare Data Representation Learning
by: Huang, Chun-Kai, et al.
Published: (2024)

DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly Detection
by: Zhang, Wenxin, et al.
Published: (2025)

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

Frequency Adaptive Normalization For Non-stationary Time Series Forecasting
by: Ye, Weiwei, et al.
Published: (2024)

Deconfounded Time Series Forecasting: A Causal Inference Approach
by: Gao, Wentao, et al.
Published: (2024)

Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series
by: Chang, Ching, et al.
Published: (2024)

Non-Stationarity in the Embedding Space of Time Series Foundation Models
by: Choi, Jinmyeong, et al.
Published: (2026)

A Survey on Deep Learning based Time Series Analysis with Frequency Transformation
by: Yi, Kun, et al.
Published: (2023)

Learning to Embed Time Series Patches Independently
by: Lee, Seunghan, et al.
Published: (2023)

Toward Physics-guided Time Series Embedding
by: Hu, Jiaxi, et al.
Published: (2024)

Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
by: Xie, Shifeng, et al.
Published: (2025)

FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series Classification
by: Tian, Tian, et al.
Published: (2025)

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

FreqLens: Interpretable Frequency Attribution for Time Series Forecasting
by: Chen, Chi-Sheng, et al.
Published: (2026)

Universal Time-Series Representation Learning: A Survey
by: Trirat, Patara, et al.
Published: (2024)

STEP: Learning STructured Embeddings for Progressive Time Series
by: Thil, Lucas, et al.
Published: (2026)

Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
by: Nguyen, Huu Hiep, et al.
Published: (2026)

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

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

Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
by: Yang, Runze, et al.
Published: (2025)

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

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

EXCON: Extreme Instance-based Contrastive Representation Learning of Severely Imbalanced Multivariate Time Series for Solar Flare Prediction
by: Vural, Onur, et al.
Published: (2024)

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

Time Series Diffusion in the Frequency Domain
by: Crabbé, Jonathan, et al.
Published: (2024)

GRE^2-MDCL: Graph Representation Embedding Enhanced via Multidimensional Contrastive Learning
by: Fan, Kaizhe, et al.
Published: (2024)