Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
Fuente:
arXiv
Saved in:
| Main Authors: | Ekambaram, Vijay, Jati, Arindam, Dayama, Pankaj, Mukherjee, Sumanta, Nguyen, Nam H., Gifford, Wesley M., Reddy, Chandra, Kalagnanam, Jayant |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis
by: Ekambaram, Vijay, et al.
Published: (2025)
by: Ekambaram, Vijay, et al.
Published: (2025)
Towards Unbiased Evaluation of Time-series Anomaly Detector
by: Bhattacharya, Debarpan, et al.
Published: (2024)
by: Bhattacharya, Debarpan, et al.
Published: (2024)
Activations Through Extensions: A Framework To Boost Performance Of Neural Networks
by: Kamanchi, Chandramouli, et al.
Published: (2024)
by: Kamanchi, Chandramouli, et al.
Published: (2024)
Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models
by: Wen, Yunshi, et al.
Published: (2026)
by: Wen, Yunshi, et al.
Published: (2026)
Using Pre-trained LLMs for Multivariate Time Series Forecasting
by: Wolff, Malcolm L., et al.
Published: (2025)
by: Wolff, Malcolm L., et al.
Published: (2025)
PreMixer: MLP-Based Pre-training Enhanced MLP-Mixers for Large-scale Traffic Forecasting
by: Zhang, Tongtong, et al.
Published: (2024)
by: Zhang, Tongtong, et al.
Published: (2024)
Mixing It Up: Exploring Mixer Networks for Irregular Multivariate Time Series Forecasting
by: Klötergens, Christian, et al.
Published: (2025)
by: Klötergens, Christian, et al.
Published: (2025)
xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories
by: Kraus, Maurice, et al.
Published: (2024)
by: Kraus, Maurice, et al.
Published: (2024)
Learning to Shuffle: Block Reshuffling and Reversal Schemes for Stochastic Optimization
by: Nguyen, Lam M., et al.
Published: (2026)
by: Nguyen, Lam M., et al.
Published: (2026)
Lightweight Object Detection Using Quantized YOLOv4-Tiny for Emergency Response in Aerial Imagery
by: Boddu, Sindhu, et al.
Published: (2025)
by: Boddu, Sindhu, et al.
Published: (2025)
U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting
by: Ma, Xiang, et al.
Published: (2024)
by: Ma, Xiang, et al.
Published: (2024)
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
by: Wang, Shiyu, et al.
Published: (2024)
by: Wang, Shiyu, et al.
Published: (2024)
Efficient Edge Deployment of Quantized YOLOv4-Tiny for Aerial Emergency Object Detection on Raspberry Pi 5
by: Boddu, Sindhu, et al.
Published: (2025)
by: Boddu, Sindhu, et al.
Published: (2025)
Leveraging Spatiotemporal Graph Neural Networks for Multi-Store Sales Forecasting
by: Singh, Manish, et al.
Published: (2025)
by: Singh, Manish, et al.
Published: (2025)
Efficient Embedding-based Synthetic Data Generation for Complex Reasoning Tasks
by: Jayaraman, Srideepika, et al.
Published: (2026)
by: Jayaraman, Srideepika, et al.
Published: (2026)
SDMixer: Sparse Dual-Mixer for Time Series Forecasting
by: Ao, Xiang
Published: (2026)
by: Ao, Xiang
Published: (2026)
Pre-trained Forecasting Models: Strong Zero-Shot Feature Extractors for Time Series Classification
by: Auer, Andreas, et al.
Published: (2025)
by: Auer, Andreas, et al.
Published: (2025)
Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting
by: Madarasingha, Chamara, et al.
Published: (2025)
by: Madarasingha, Chamara, et al.
Published: (2025)
Volatility Forecasting in Global Financial Markets Using TimeMixer
by: Li, Alex
Published: (2024)
by: Li, Alex
Published: (2024)
LLM-Mixer: Multiscale Mixing in LLMs for Time Series Forecasting
by: Kowsher, Md, et al.
Published: (2024)
by: Kowsher, Md, et al.
Published: (2024)
Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series
by: Murad, Md Mahmuddun Nabi, et al.
Published: (2025)
by: Murad, Md Mahmuddun Nabi, et al.
Published: (2025)
Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting
by: Zhou, Ziyu, et al.
Published: (2025)
by: Zhou, Ziyu, et al.
Published: (2025)
MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMs
by: Chatzigeorgakidis, Georgios, et al.
Published: (2024)
by: Chatzigeorgakidis, Georgios, et al.
Published: (2024)
Pre-training Epidemic Time Series Forecasters with Compartmental Prototypes
by: Liu, Zewen, et al.
Published: (2025)
by: Liu, Zewen, et al.
Published: (2025)
Causal-Aware Foundation-Model for Bilevel Optimization in Discrete Choice Settings
by: Subramanian, Shivaram, et al.
Published: (2026)
by: Subramanian, Shivaram, et al.
Published: (2026)
Deep Policy Iteration with Integer Programming for Inventory Management
by: Harsha, Pavithra, et al.
Published: (2021)
by: Harsha, Pavithra, et al.
Published: (2021)
Toward a Trustworthy Optimization Modeling Agent via Verifiable Synthetic Data Generation
by: Lima, Vinicius, et al.
Published: (2025)
by: Lima, Vinicius, et al.
Published: (2025)
Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay
by: Jagirdar, Hussain, et al.
Published: (2025)
by: Jagirdar, Hussain, et al.
Published: (2025)
A unified equation for saturation magnetization and spin transport in weakly disordered ferromagnets
by: Mukherjee, Sumanta
Published: (2026)
by: Mukherjee, Sumanta
Published: (2026)
Spontaneous Emission, Free Energy, and Relaxation-Limited Processes in Setting Limits on Solar Energy Conversion Efficiency
by: Mukherjee, Sumanta
Published: (2026)
by: Mukherjee, Sumanta
Published: (2026)
Magnetic Behavior of Ferro-, Antiferro-, and Ferrimagnetic Systems in the Griffiths Phase: A Theoretical Study
by: Mukherjee, Sumanta
Published: (2026)
by: Mukherjee, Sumanta
Published: (2026)
FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting
by: Ouyang, Pengpeng, et al.
Published: (2025)
by: Ouyang, Pengpeng, et al.
Published: (2025)
Prompt Tuning with Diffusion for Few-Shot Pre-trained Policy Generalization
by: Hu, Shengchao, et al.
Published: (2024)
by: Hu, Shengchao, et al.
Published: (2024)
Synergistic Anchored Contrastive Pre-training for Few-Shot Relation Extraction
by: Luo, Da, et al.
Published: (2023)
by: Luo, Da, et al.
Published: (2023)
Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners
by: Park, Keon-Hee, et al.
Published: (2024)
by: Park, Keon-Hee, et al.
Published: (2024)
DPWMixer: Dual-Path Wavelet Mixer for Long-Term Time Series Forecasting
by: Qianyang, Li, et al.
Published: (2025)
by: Qianyang, Li, et al.
Published: (2025)
TSKANMixer: Kolmogorov-Arnold Networks with MLP-Mixer Model for Time Series Forecasting
by: Hong, Young-Chae, et al.
Published: (2025)
by: Hong, Young-Chae, et al.
Published: (2025)
WindowMixer: Intra-Window and Inter-Window Modeling for Time Series Forecasting
by: Liu, Quangao, et al.
Published: (2024)
by: Liu, Quangao, et al.
Published: (2024)
Enchimento do reservatório de Santa Clara, rio Jordão (Pr), bacia hidrográfica do rio Iguaçu : efeitos sobre a comunidade fitoplanctônica.
by: Jati, Susicley
Published: (2010)
by: Jati, Susicley
Published: (2010)
TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
by: Song, Ziyang, et al.
Published: (2023)
by: Song, Ziyang, et al.
Published: (2023)
Similar Items
-
TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis
by: Ekambaram, Vijay, et al.
Published: (2025) -
Towards Unbiased Evaluation of Time-series Anomaly Detector
by: Bhattacharya, Debarpan, et al.
Published: (2024) -
Activations Through Extensions: A Framework To Boost Performance Of Neural Networks
by: Kamanchi, Chandramouli, et al.
Published: (2024) -
Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models
by: Wen, Yunshi, et al.
Published: (2026) -
Using Pre-trained LLMs for Multivariate Time Series Forecasting
by: Wolff, Malcolm L., et al.
Published: (2025)