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20182026
most citedLightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation -- Extended Version

102 citations · 211 across the 70 of their papers we have counts for

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64 papers · 1 filter

cs.LG2026

UniWind: Toward Unified Day-Ahead Wind Power Forecasting via Physics-Informed State Routing

Ronghui Xu, Tongxin Wu, Guozhen Zhang +4

Day-ahead wind power forecasting is essential for cost-effective power-system operation. It is primarily driven by future meteorological conditions while retaining temporal depende…

cs.LG2026

Time Series Causal Discovery via Context-Conditioned and Causality-Augmented Pretraining

Biao Ouyang, Tengxue Zhang, Zhihao Zhuang +3

Causal discovery from time series is critical for many real-world applications, such as tracing the root causes of anomalies. Existing approaches typically rely on dataset-specific…

cs.LG2026

TiWeaver: Unified Temporal Dynamics Modeling via Contextual Patching

Zhe Li, Jindong Tian, Hao Miao +3

Multivariate time series forecasting plays a critical role in real-world applications, including weather prediction, stock analysis, and health monitoring. Due to the diversity of…

cs.LG2026

TimeBlocks: Foundational and Continual Time-Series Blockbase -- Extended Version

David Campos, Bin Yang, Tung Kieu +3

The ongoing digitization has led to a proliferation of time-series data streams that monitor a variety of processes, from which valuable insights may be obtained. Further, the emer…

cs.LG2026

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models

Xingjian Wu, Junkai Lu, Siyu Yan +4

Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existing MAS typically rely on pre…

cs.LG2026

GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables

Zhengyu Li, Xiangfei Qiu, Yuhan Zhu +4

Exogenous variables offer valuable supplementary information for predicting future endogenous variables. Forecasting with exogenous variables needs to consider both past-to-future…