Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density
Fuente:
arXiv
Saved in:
| Main Authors: | Fei, Jingru, Yi, Kun, Wang, Alex Xing, Wen, Qingsong, Zhu, Xiangxiang, Fan, Wei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting
by: Fei, Jingru, et al.
Published: (2025)
by: Fei, Jingru, et al.
Published: (2025)
FilterNet: Harnessing Frequency Filters for Time Series Forecasting
by: Yi, Kun, et al.
Published: (2024)
by: Yi, Kun, et al.
Published: (2024)
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
by: Liu, Qingxiang, et al.
Published: (2024)
by: Liu, Qingxiang, et al.
Published: (2024)
Foundation Models for Time Series Analysis: A Tutorial and Survey
by: Liang, Yuxuan, et al.
Published: (2024)
by: Liang, Yuxuan, et al.
Published: (2024)
MedGNN: Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification
by: Fan, Wei, et al.
Published: (2025)
by: Fan, Wei, et al.
Published: (2025)
LogoRA: Local-Global Representation Alignment for Robust Time Series Classification
by: Zhang, Huanyu, et al.
Published: (2024)
by: Zhang, Huanyu, et al.
Published: (2024)
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
by: Shi, Xiaoming, et al.
Published: (2024)
by: Shi, Xiaoming, et al.
Published: (2024)
NuwaTS: a Foundation Model Mending Every Incomplete Time Series
by: Cheng, Jinguo, et al.
Published: (2024)
by: Cheng, Jinguo, et al.
Published: (2024)
SEMPO: Lightweight Foundation Models for Time Series Forecasting
by: He, Hui, et al.
Published: (2025)
by: He, Hui, et al.
Published: (2025)
Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
by: Qiao, Zhongzheng, et al.
Published: (2025)
by: Qiao, Zhongzheng, et al.
Published: (2025)
Foundation Models for Education: Promises and Prospects
by: Xu, Tianlong, et al.
Published: (2024)
by: Xu, Tianlong, et al.
Published: (2024)
Unlocking the Power of LSTM for Long Term Time Series Forecasting
by: Kong, Yaxuan, et al.
Published: (2024)
by: Kong, Yaxuan, et al.
Published: (2024)
A Survey on Deep Learning based Time Series Analysis with Frequency Transformation
by: Yi, Kun, et al.
Published: (2023)
by: Yi, Kun, et al.
Published: (2023)
TimeRadar: A Domain-Rotatable Foundation Model for Time Series Anomaly Detection
by: He, Hui, et al.
Published: (2026)
by: He, Hui, et al.
Published: (2026)
Task-oriented Time Series Imputation Evaluation via Generalized Representers
by: Wang, Zhixian, et al.
Published: (2024)
by: Wang, Zhixian, et al.
Published: (2024)
Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
by: Zhang, YiFan, et al.
Published: (2024)
by: Zhang, YiFan, et al.
Published: (2024)
TS-Memory: Plug-and-Play Memory for Time Series Foundation Models
by: Lyu, Sisuo, et al.
Published: (2026)
by: Lyu, Sisuo, et al.
Published: (2026)
GraphSubDetector: Time Series Subsequence Anomaly Detection via Density-Aware Adaptive Graph Neural Network
by: Chen, Weiqi, et al.
Published: (2024)
by: Chen, Weiqi, et al.
Published: (2024)
Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models
by: Liu, Xu, et al.
Published: (2025)
by: Liu, Xu, et al.
Published: (2025)
Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution Shifts
by: Qin, Dalin, et al.
Published: (2024)
by: Qin, Dalin, et al.
Published: (2024)
ViTime: Foundation Model for Time Series Forecasting Powered by Vision Intelligence
by: Yang, Luoxiao, et al.
Published: (2024)
by: Yang, Luoxiao, et al.
Published: (2024)
Beyond Extrapolation: Knowledge Utilization Paradigm with Bidirectional Inspiration for Time Series Forecasting
by: Chong, Liu, et al.
Published: (2026)
by: Chong, Liu, et al.
Published: (2026)
CaPulse: Detecting Anomalies by Tuning in to the Causal Rhythms of Time Series
by: Xia, Yutong, et al.
Published: (2025)
by: Xia, Yutong, et al.
Published: (2025)
HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting
by: Zhao, Shubao, et al.
Published: (2024)
by: Zhao, Shubao, et al.
Published: (2024)
TimeMar: Multi-Scale Autoregressive Modeling for Unconditional Time Series Generation
by: Xu, Xiangyu, et al.
Published: (2026)
by: Xu, Xiangyu, et al.
Published: (2026)
Diversified Scaling Inference in Time Series Foundation Models
by: Hua, Ruijin, et al.
Published: (2026)
by: Hua, Ruijin, et al.
Published: (2026)
Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting
by: Hu, Jiaxi, et al.
Published: (2024)
by: Hu, Jiaxi, et al.
Published: (2024)
Causal Time Series Generation via Diffusion Models
by: Xia, Yutong, et al.
Published: (2025)
by: Xia, Yutong, et al.
Published: (2025)
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
by: Cheng, Hao, et al.
Published: (2024)
by: Cheng, Hao, et al.
Published: (2024)
Brain Foundation Models: A Survey on Advancements in Neural Signal Processing and Brain Discovery
by: Zhou, Xinliang, et al.
Published: (2025)
by: Zhou, Xinliang, et al.
Published: (2025)
ASGMamba: Adaptive Spectral Gating Mamba for Multivariate Time Series Forecasting
by: Li, Qianyang, et al.
Published: (2026)
by: Li, Qianyang, et al.
Published: (2026)
PyPOTS: A Python Toolkit for Machine Learning on Partially-Observed Time Series
by: Du, Wenjie, et al.
Published: (2023)
by: Du, Wenjie, et al.
Published: (2023)
Transformers and Their Roles as Time Series Foundation Models
by: Wu, Dennis, et al.
Published: (2025)
by: Wu, Dennis, et al.
Published: (2025)
TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting
by: Zhang, Huanyu, et al.
Published: (2024)
by: Zhang, Huanyu, et al.
Published: (2024)
Frequency Matters: When Time Series Foundation Models Fail Under Spectral Shift
by: Wang, Tianze, et al.
Published: (2025)
by: Wang, Tianze, et al.
Published: (2025)
Cross-Domain Conditional Diffusion Models for Time Series Imputation
by: Zhang, Kexin, et al.
Published: (2025)
by: Zhang, Kexin, et al.
Published: (2025)
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting
by: Xue, Wang, et al.
Published: (2023)
by: Xue, Wang, et al.
Published: (2023)
Explaining Time Series via Contrastive and Locally Sparse Perturbations
by: Liu, Zichuan, et al.
Published: (2024)
by: Liu, Zichuan, et al.
Published: (2024)
Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting
by: Zhou, Ziyu, et al.
Published: (2025)
by: Zhou, Ziyu, et al.
Published: (2025)
Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
by: Jin, Ming, et al.
Published: (2023)
by: Jin, Ming, et al.
Published: (2023)
Similar Items
-
Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting
by: Fei, Jingru, et al.
Published: (2025) -
FilterNet: Harnessing Frequency Filters for Time Series Forecasting
by: Yi, Kun, et al.
Published: (2024) -
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
by: Liu, Qingxiang, et al.
Published: (2024) -
Foundation Models for Time Series Analysis: A Tutorial and Survey
by: Liang, Yuxuan, et al.
Published: (2024) -
MedGNN: Towards Multi-resolution Spatiotemporal Graph Learning for Medical Time Series Classification
by: Fan, Wei, et al.
Published: (2025)