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| CatNet: Controlling the False Discovery Rate in LSTM with SHAP Feature Importance and Gaussian Mirrors | Nov 25, 2024 | Feature Importancefeature selection | —Unverified | 0 |
| LeMoLE: LLM-Enhanced Mixture of Linear Experts for Time Series Forecasting | Nov 24, 2024 | Computational EfficiencyNatural Language Understanding | —Unverified | 0 |
| Research on Optimal Portfolio Based on Multifractal Features | Nov 24, 2024 | Time Series | —Unverified | 0 |
| Tackling Data Heterogeneity in Federated Time Series Forecasting | Nov 24, 2024 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via Large Language Models | Nov 24, 2024 | Problem DecompositionTime Series | CodeCode Available | 1 |
| Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting | Nov 24, 2024 | Few-Shot LearningSynthetic Data Generation | —Unverified | 0 |
| Quantile deep learning models for multi-step ahead time series prediction | Nov 24, 2024 | Deep LearningPrediction | CodeCode Available | 0 |
| A Unified Energy Management Framework for Multi-Timescale Forecasting in Smart Grids | Nov 22, 2024 | energy managementLoad Forecasting | —Unverified | 0 |
| Exploring Kolmogorov-Arnold Networks for Interpretable Time Series Classification | Nov 22, 2024 | ClassificationComputational Efficiency | CodeCode Available | 0 |
