Towards Principled Test-Time Adaptation for Time Series Forecasting
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Haochun, Xu, Ruichen, Kementzidis, Georgios, Cho, Karen, Villarreal, Sebastian Ramirez, Deng, Yuefan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
An Iterative Framework for Generative Backmapping of Coarse Grained Proteins
por: Kementzidis, Georgios, et al.
Publicado: (2025)
por: Kementzidis, Georgios, et al.
Publicado: (2025)
Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks
por: Wu, Zongyu, et al.
Publicado: (2025)
por: Wu, Zongyu, et al.
Publicado: (2025)
The Impact of Move Schemes on Simulated Annealing Performance
por: Xu, Ruichen, et al.
Publicado: (2025)
por: Xu, Ruichen, et al.
Publicado: (2025)
Velocity-Inferred Hamiltonian Neural Networks: Learning Energy-Conserving Dynamics from Position-Only Data
por: Xu, Ruichen, et al.
Publicado: (2025)
por: Xu, Ruichen, et al.
Publicado: (2025)
Accurate Parameter-Efficient Test-Time Adaptation for Time Series Forecasting
por: Medeiros, Heitor R., et al.
Publicado: (2025)
por: Medeiros, Heitor R., et al.
Publicado: (2025)
AdaNODEs: Test Time Adaptation for Time Series Forecasting Using Neural ODEs
por: Dang, Ting, et al.
Publicado: (2026)
por: Dang, Ting, et al.
Publicado: (2026)
Test Time Learning for Time Series Forecasting
por: Christou, Panayiotis, et al.
Publicado: (2024)
por: Christou, Panayiotis, et al.
Publicado: (2024)
STEPS: A Temporal Smooth Error Propagation Solver on the Manifolds for Test-Time Adaptation in Time Series Forecasting
por: Liu, Jiaqi, et al.
Publicado: (2026)
por: Liu, Jiaqi, et al.
Publicado: (2026)
Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation
por: Kim, HyunGi, et al.
Publicado: (2025)
por: Kim, HyunGi, et al.
Publicado: (2025)
Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting
por: Kayaalp, Mert, et al.
Publicado: (2025)
por: Kayaalp, Mert, et al.
Publicado: (2025)
DAM: Towards A Foundation Model for Time Series Forecasting
por: Darlow, Luke, et al.
Publicado: (2024)
por: Darlow, Luke, et al.
Publicado: (2024)
Causal Time-Series Synchronization for Multi-Dimensional Forecasting
por: Mayr, Michael, et al.
Publicado: (2024)
por: Mayr, Michael, et al.
Publicado: (2024)
Nonstationary Time Series Forecasting via Unknown Distribution Adaptation
por: Li, Zijian, et al.
Publicado: (2024)
por: Li, Zijian, et al.
Publicado: (2024)
Channel-Aware Low-Rank Adaptation in Time Series Forecasting
por: Nie, Tong, et al.
Publicado: (2024)
por: Nie, Tong, et al.
Publicado: (2024)
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
por: Liu, Qingxiang, et al.
Publicado: (2024)
por: Liu, Qingxiang, et al.
Publicado: (2024)
Test-Time Adaptation for Non-stationary Time Series: From Synthetic Regime Shifts to Financial Markets
por: Wu, Yurui, et al.
Publicado: (2026)
por: Wu, Yurui, et al.
Publicado: (2026)
Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting
por: Pan, Licheng, et al.
Publicado: (2025)
por: Pan, Licheng, et al.
Publicado: (2025)
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting
por: Deng, Jinliang, et al.
Publicado: (2023)
por: Deng, Jinliang, et al.
Publicado: (2023)
Towards Invariant Time Series Forecasting in Smart Cities
por: Zhang, Ziyi, et al.
Publicado: (2024)
por: Zhang, Ziyi, et al.
Publicado: (2024)
It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
por: Qiao, Zhongzheng, et al.
Publicado: (2026)
por: Qiao, Zhongzheng, et al.
Publicado: (2026)
EBV: Electronic Bee-Veterinarian for Principled Mining and Forecasting of Honeybee Time Series
por: Hossain, Mst. Shamima, et al.
Publicado: (2024)
por: Hossain, Mst. Shamima, et al.
Publicado: (2024)
Fidel-TS: A High-Fidelity Multimodal Benchmark for Time Series Forecasting
por: Xu, Zhijian, et al.
Publicado: (2025)
por: Xu, Zhijian, et al.
Publicado: (2025)
Boundary-Informed Method of Lines for Physics Informed Neural Networks
por: Cederholm, Maximilian, et al.
Publicado: (2025)
por: Cederholm, Maximilian, et al.
Publicado: (2025)
Selective Learning for Deep Time Series Forecasting
por: Fu, Yisong, et al.
Publicado: (2025)
por: Fu, Yisong, et al.
Publicado: (2025)
MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMs
por: Chatzigeorgakidis, Georgios, et al.
Publicado: (2024)
por: Chatzigeorgakidis, Georgios, et al.
Publicado: (2024)
Is Mamba Effective for Time Series Forecasting?
por: Wang, Zihan, et al.
Publicado: (2024)
por: Wang, Zihan, et al.
Publicado: (2024)
Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting
por: Fu, Xinghong, et al.
Publicado: (2026)
por: Fu, Xinghong, et al.
Publicado: (2026)
A Lightweight Sparse Interaction Network for Time Series Forecasting
por: Zhang, Xu, et al.
Publicado: (2026)
por: Zhang, Xu, et al.
Publicado: (2026)
Ellipsoidal Time Series Forecasting
por: Wang, Qilin
Publicado: (2025)
por: Wang, Qilin
Publicado: (2025)
TimeSAF: Towards LLM-Guided Semantic Asynchronous Fusion for Time Series Forecasting
por: Zhang, Fan, et al.
Publicado: (2026)
por: Zhang, Fan, et al.
Publicado: (2026)
Aurora: Towards Universal Generative Multimodal Time Series Forecasting
por: Wu, Xingjian, et al.
Publicado: (2025)
por: Wu, Xingjian, et al.
Publicado: (2025)
Panda: Test-Time Adaptation with Negative Data Augmentation
por: Deng, Ruxi, et al.
Publicado: (2025)
por: Deng, Ruxi, et al.
Publicado: (2025)
Time Series Forecastability Measures
por: Wang, Rui, et al.
Publicado: (2025)
por: Wang, Rui, et al.
Publicado: (2025)
Sparse Transformer with Local and Seasonal Adaptation for Multivariate Time Series Forecasting
por: Zhang, Yifan, et al.
Publicado: (2023)
por: Zhang, Yifan, et al.
Publicado: (2023)
Two Simple Principles for Diffusion-Based Test-Time Adaptation
por: Song, Kaiyu, et al.
Publicado: (2023)
por: Song, Kaiyu, et al.
Publicado: (2023)
Subspace Optimization for Backpropagation-Free Continual Test-Time Adaptation
por: Sójka, Damian, et al.
Publicado: (2026)
por: Sójka, Damian, et al.
Publicado: (2026)
Towards Non-Stationary Time Series Forecasting with Temporal Stabilization and Frequency Differencing
por: Lu, Junkai, et al.
Publicado: (2025)
por: Lu, Junkai, et al.
Publicado: (2025)
Amortized Predictability-aware Training Framework for Time Series Forecasting and Classification
por: Zhang, Xu, et al.
Publicado: (2026)
por: Zhang, Xu, et al.
Publicado: (2026)
Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptations
por: Germán-Morales, M., et al.
Publicado: (2024)
por: Germán-Morales, M., et al.
Publicado: (2024)
Forecasting with Guidance: Representation-Level Supervision for Time Series Forecasting
por: Wang, Jiacheng, et al.
Publicado: (2026)
por: Wang, Jiacheng, et al.
Publicado: (2026)
Ejemplares similares
-
An Iterative Framework for Generative Backmapping of Coarse Grained Proteins
por: Kementzidis, Georgios, et al.
Publicado: (2025) -
Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks
por: Wu, Zongyu, et al.
Publicado: (2025) -
The Impact of Move Schemes on Simulated Annealing Performance
por: Xu, Ruichen, et al.
Publicado: (2025) -
Velocity-Inferred Hamiltonian Neural Networks: Learning Energy-Conserving Dynamics from Position-Only Data
por: Xu, Ruichen, et al.
Publicado: (2025) -
Accurate Parameter-Efficient Test-Time Adaptation for Time Series Forecasting
por: Medeiros, Heitor R., et al.
Publicado: (2025)