explainable AI 1information bottleneck 1interpretability 1sparse explanations 1time series forecasting 1
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cs.LG2026
Information Bottleneck Learning for Faithful Time Series Forecasting Explanations
Xu Zheng, Wei Cheng, Zhuomin Chen +3
The paper presents IB-Forecast, an interpretable multivariate time-series forecasting model that uses an information bottleneck to generate sparse, faithful explanations of predict…
cs.LG2026
MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters
Aitian Ma, Dongsheng Luo, Mo Sha
Recently, there has been a growing interest in Long-term Time Series Forecasting (LTSF), which involves predicting long-term future values by analyzing a large amount of historical…
cs.LG2024
MMFNet: Multi-Scale Frequency Masking Neural Network for Multivariate Time Series Forecasting
Aitian Ma, Dongsheng Luo, Mo Sha
Long-term Time Series Forecasting (LTSF) is critical for numerous real-world applications, such as electricity consumption planning, financial forecasting, and disease propagation…