Electricity
Canonical13papers using it
2021first seen
The 'Electricity' dataset is a multivariate time series dataset used to evaluate forecasting methods by capturing the interdependencies among different variables over time.
Papers using Electricity (13)
- Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series PredictionEnTransformer: A Deep Generative Transformer for Multivariate Probabilistic ForecastingA Decomposition-based State Space Model for Multivariate Time-Series ForecastingDDT: A Dual-Masking Dual-Expert Transformer for Energy Time-Series ForecastingContrastive Time Series Forecasting with AnomaliesSTaTS: Structure-Aware Temporal Sequence Summarization via Statistical Window MergingInvDec: Inverted Decoder for Multivariate Time Series Forecasting with Separated Temporal and Variate ModelingAdaMixT: Adaptive Weighted Mixture of Multi-Scale Expert Transformers for Time Series ForecastingReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series ForecastingInstance-wise Graph-based Framework for Multivariate Time Series ForecastingHow Much Can Time-related Features Enhance Time Series Forecasting?Test Time Learning for Time Series ForecastingTransformer Multivariate Forecasting: Less is More?