Image de couverture de livre

ADAPTive Input Training for Many-to-One Pre-Training on Time-Series Classification

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Quinlan, Paul, Li, Qingguo, Zhu, Xiaodan
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Chronicle: A Multimodal Foundation Model for Joint Language and Time Series Understanding
par: Quinlan, Paul, et autres
Publié: (2026)

Chat-TS: Enhancing Multi-Modal Reasoning Over Time-Series and Natural Language Data
par: Quinlan, Paul, et autres
Publié: (2025)

A Survey on Time-Series Pre-Trained Models
par: Ma, Qianli, et autres
Publié: (2023)

TiCT: A Synthetically Pre-Trained Foundation Model for Time Series Classification
par: Yeh, Chin-Chia Michael, et autres
Publié: (2025)

Interpretable Pre-Trained Transformers for Heart Time-Series Data
par: Davies, Harry J., et autres
Publié: (2024)

Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturing
par: Lee, Sewoong, et autres
Publié: (2023)

TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis
par: Ekambaram, Vijay, et autres
Publié: (2025)

One Transformer for All Time Series: Representing and Training with Time-Dependent Heterogeneous Tabular Data
par: Luetto, Simone, et autres
Publié: (2023)

Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
par: Zhang, Weijia, et autres
Publié: (2024)

Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification
par: Farsang, Mónika, et autres
Publié: (2026)

DELPHYNE: A Pre-Trained Model for General and Financial Time Series
par: Ding, Xueying, et autres
Publié: (2025)

Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting
par: Sartipi, Timothée Hornek Amir, et autres
Publié: (2025)

SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series Forecasting
par: Huang, Ting-Ji, et autres
Publié: (2025)

Reasoning-Aware Training for Time Series Forecasting
par: Ahamed, Md Atik, et autres
Publié: (2026)

A Time Series Multitask Framework Integrating a Large Language Model, Pre-Trained Time Series Model, and Knowledge Graph
par: Hao, Shule, et autres
Publié: (2025)

Train Once, Answer All: Many Pretraining Experiments for the Cost of One
par: Bordt, Sebastian, et autres
Publié: (2025)

Provably Robust Pre-Trained Ensembles for Biomarker-Based Cancer Classification
par: Lee, Chongmin, et autres
Publié: (2024)

Analyzing Generalization in Pre-Trained Symbolic Regression
par: Voigt, Henrik, et autres
Publié: (2025)

TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models
par: Wang, Jiahao, et autres
Publié: (2024)

Training and Evaluating Causal Forecasting Models for Time-Series
par: Crasson, Thomas, et autres
Publié: (2024)

Unified Training of Universal Time Series Forecasting Transformers
par: Woo, Gerald, et autres
Publié: (2024)

Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection
par: Xu, Hongzuo, et autres
Publié: (2022)

KAIROS: Unified Training for Universal Non-Autoregressive Time Series Forecasting
par: Ding, Kuiye, et autres
Publié: (2025)

On-device AI: Quantization-aware Training of Transformers in Time-Series
par: Ling, Tianheng, et autres
Publié: (2024)

Long Input Sequence Network for Long Time Series Forecasting
par: Ma, Chao, et autres
Publié: (2024)

One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning
par: Zhang, Haozhen, et autres
Publié: (2024)

Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models
par: Schröder, Christopher, et autres
Publié: (2024)

Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
par: Wang, Hao, et autres
Publié: (2025)

COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classification
par: Barreda, Jesus, et autres
Publié: (2024)

Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One
par: Zhang, Hongyuan, et autres
Publié: (2023)

TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learning
par: Zhang, Junru, et autres
Publié: (2025)

One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
par: Gao, Mengzhou, et autres
Publié: (2026)

TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
par: Song, Ziyang, et autres
Publié: (2023)

Optimizing the Training Diet: Data Mixture Search for Robust Time Series Forecasting
par: Pennino, Federico, et autres
Publié: (2025)

Reinforcement Learning on Pre-Training Data
par: Li, Siheng, et autres
Publié: (2025)

PTMs-TSCIL Pre-Trained Models Based Class-Incremental Learning
par: Wu, Yuanlong, et autres
Publié: (2025)

Large EEG-U-Transformer for Time-Step Level Detection Without Pre-Training
par: Wu, Kerui, et autres
Publié: (2025)

Value-Based Pre-Training with Downstream Feedback
par: Ke, Shuqi, et autres
Publié: (2026)

Layer Importance for Mathematical Reasoning is Forged in Pre-Training and Invariant after Post-Training
par: Nepal, Aadim, et autres
Publié: (2025)

Open-World Test-Time Training: Self-Training with Contrast Learning
par: Su, Houcheng, et autres
Publié: (2024)