DeCoP: Enhancing Self-Supervised Time Series Representation with Dependency Controlled Pre-training
Fuente:
arXiv
Guardado en:
| Autores principales: | Wu, Yuemin, Wu, Zhongze, Su, Xiu, Yang, Feng, Xu, Hongyan, Lin, Xi, Huang, Wenti, You, Shan, Xu, Chang |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Graph Unlearning Meets Influence-aware Negative Preference Optimization
por: Chen, Qiang, et al.
Publicado: (2025)
por: Chen, Qiang, et al.
Publicado: (2025)
VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model
por: Li, Wenhao, et al.
Publicado: (2026)
por: Li, Wenhao, et al.
Publicado: (2026)
Enhancing SAR Object Detection with Self-Supervised Pre-training on Masked Auto-Encoders
por: Pu, Xinyang, et al.
Publicado: (2025)
por: Pu, Xinyang, et al.
Publicado: (2025)
Self-Supervised Dynamical System Representations for Physiological Time-Series
por: Chen, Yenho, et al.
Publicado: (2025)
por: Chen, Yenho, et al.
Publicado: (2025)
Effect of Rotation Angle in Self-Supervised Pre-training is Dataset-Dependent
por: Saranchuk, Amy, et al.
Publicado: (2024)
por: Saranchuk, Amy, et al.
Publicado: (2024)
Identify, Isolate, and Purge: Mitigating Hallucinations in LVLMs via Self-Evolving Distillation
por: Li, Wenhao, et al.
Publicado: (2025)
por: Li, Wenhao, et al.
Publicado: (2025)
Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series
por: Chang, Ching, et al.
Publicado: (2024)
por: Chang, Ching, et al.
Publicado: (2024)
Selective Masking based Self-Supervised Learning for Image Semantic Segmentation
por: Wang, Yuemin, et al.
Publicado: (2025)
por: Wang, Yuemin, et al.
Publicado: (2025)
AdaMR: Adaptable Molecular Representation for Unified Pre-training Strategy
por: Ding, Yan, et al.
Publicado: (2023)
por: Ding, Yan, et al.
Publicado: (2023)
Enhancing Semantic Segmentation with Continual Self-Supervised Pre-training
por: Ebouky, Brown, et al.
Publicado: (2025)
por: Ebouky, Brown, et al.
Publicado: (2025)
Sentinel-VLA: A Metacognitive VLA Model with Active Status Monitoring for Dynamic Reasoning and Error Recovery
por: Li, Wenhao, et al.
Publicado: (2026)
por: Li, Wenhao, et al.
Publicado: (2026)
Quantifying the Pre-training Dividend: Generative versus Latent Self-Supervised Learning for Time Series Foundation Models
por: Major, Noam, et al.
Publicado: (2026)
por: Major, Noam, et al.
Publicado: (2026)
MetaDD: Boosting Dataset Distillation with Neural Network Architecture-Invariant Generalization
por: Zhao, Yunlong, et al.
Publicado: (2024)
por: Zhao, Yunlong, et al.
Publicado: (2024)
On the Asymptotics of Self-Supervised Pre-training: Two-Stage M-Estimation and Representation Symmetry
por: Tinati, Mohammad, et al.
Publicado: (2026)
por: Tinati, Mohammad, et al.
Publicado: (2026)
Cross-Domain Pre-training with Language Models for Transferable Time Series Representations
por: Cheng, Mingyue, et al.
Publicado: (2024)
por: Cheng, Mingyue, et al.
Publicado: (2024)
Self-Supervised Pre-training with Symmetric Superimposition Modeling for Scene Text Recognition
por: Gao, Zuan, et al.
Publicado: (2024)
por: Gao, Zuan, et al.
Publicado: (2024)
Weak Augmentation Guided Relational Self-Supervised Learning
por: Zheng, Mingkai, et al.
Publicado: (2022)
por: Zheng, Mingkai, et al.
Publicado: (2022)
Vortex-Enhanced Zitterbewegung in Relativistic Electron Wave Packets
por: Guo, Zhongze, et al.
Publicado: (2025)
por: Guo, Zhongze, et al.
Publicado: (2025)
In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks
por: Xu, Shangqing, et al.
Publicado: (2026)
por: Xu, Shangqing, et al.
Publicado: (2026)
LEGATO: Good Identity Unlearning Is Continuous
por: Chen, Qiang, et al.
Publicado: (2026)
por: Chen, Qiang, et al.
Publicado: (2026)
Seamless Language Expansion: Enhancing Multilingual Mastery in Self-Supervised Models
por: Xu, Jing, et al.
Publicado: (2024)
por: Xu, Jing, et al.
Publicado: (2024)
TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
por: Cheng, Mingyue, et al.
Publicado: (2023)
por: Cheng, Mingyue, et al.
Publicado: (2023)
Scenario-Agnostic Deep-Learning-Based Localization with Contrastive Self-Supervised Pre-training
por: Zhang, Lingyan, et al.
Publicado: (2025)
por: Zhang, Lingyan, et al.
Publicado: (2025)
Adaptive Training Meets Progressive Scaling: Elevating Efficiency in Diffusion Models
por: Li, Wenhao, et al.
Publicado: (2023)
por: Li, Wenhao, et al.
Publicado: (2023)
LENS: Large Pre-trained Transformer for Exploring Financial Time Series Regularities
por: Xu, Yuanjian, et al.
Publicado: (2024)
por: Xu, Yuanjian, et al.
Publicado: (2024)
Augmentation‐Free Self‐Supervised Human Activity Recognition With Attention Mechanism and Adaptive Time Series Mixer
por: Zhongwei Hou, et al.
Publicado: (2026)
por: Zhongwei Hou, et al.
Publicado: (2026)
Decoupled Video Generation with Chain of Training-free Diffusion Model Experts
por: Li, Wenhao, et al.
Publicado: (2024)
por: Li, Wenhao, et al.
Publicado: (2024)
Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask
por: Senane, Zineb, et al.
Publicado: (2024)
por: Senane, Zineb, et al.
Publicado: (2024)
PEPT: Expert Finding Meets Personalized Pre-training
por: Peng, Qiyao, et al.
Publicado: (2023)
por: Peng, Qiyao, et al.
Publicado: (2023)
TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
por: Song, Ziyang, et al.
Publicado: (2023)
por: Song, Ziyang, et al.
Publicado: (2023)
TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation
por: Wang, Daoyu, et al.
Publicado: (2024)
por: Wang, Daoyu, et al.
Publicado: (2024)
In Pursuit of Pixel Supervision for Visual Pre-training
por: Yang, Lihe, et al.
Publicado: (2025)
por: Yang, Lihe, et al.
Publicado: (2025)
Enhancing Vision-Language Pre-training with Rich Supervisions
por: Gao, Yuan, et al.
Publicado: (2024)
por: Gao, Yuan, et al.
Publicado: (2024)
CoMA: Complementary Masking and Hierarchical Dynamic Multi-Window Self-Attention in a Unified Pre-training Framework
por: Li, Jiaxuan, et al.
Publicado: (2025)
por: Li, Jiaxuan, et al.
Publicado: (2025)
MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time
por: Kang, Jikun, et al.
Publicado: (2024)
por: Kang, Jikun, et al.
Publicado: (2024)
There is No VAE: End-to-End Pixel-Space Generative Modeling via Self-Supervised Pre-training
por: Lei, Jiachen, et al.
Publicado: (2025)
por: Lei, Jiachen, et al.
Publicado: (2025)
S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning
por: Yin, Mingze, et al.
Publicado: (2024)
por: Yin, Mingze, et al.
Publicado: (2024)
Enhancing SPARQL Generation by Triplet-order-sensitive Pre-training
por: Su, Chang, et al.
Publicado: (2024)
por: Su, Chang, et al.
Publicado: (2024)
PFML: Self-Supervised Learning of Time-Series Data Without Representation Collapse
por: Vaaras, Einari, et al.
Publicado: (2024)
por: Vaaras, Einari, et al.
Publicado: (2024)
Self-Supervised Pre-training Tasks for an fMRI Time-series Transformer in Autism Detection
por: Zhou, Yinchi, et al.
Publicado: (2024)
por: Zhou, Yinchi, et al.
Publicado: (2024)
Ejemplares similares
-
Graph Unlearning Meets Influence-aware Negative Preference Optimization
por: Chen, Qiang, et al.
Publicado: (2025) -
VLA-ATTC: Adaptive Test-Time Compute for VLA Models with Relative Action Critic Model
por: Li, Wenhao, et al.
Publicado: (2026) -
Enhancing SAR Object Detection with Self-Supervised Pre-training on Masked Auto-Encoders
por: Pu, Xinyang, et al.
Publicado: (2025) -
Self-Supervised Dynamical System Representations for Physiological Time-Series
por: Chen, Yenho, et al.
Publicado: (2025) -
Effect of Rotation Angle in Self-Supervised Pre-training is Dataset-Dependent
por: Saranchuk, Amy, et al.
Publicado: (2024)