Traffic
Canonical14papers using it
2021first seen
The 'Traffic' dataset is a multivariate time series benchmark used to evaluate forecasting methods in the context of traffic-related data.
Papers using Traffic (14)
- Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series PredictionEnTransformer: A Deep Generative Transformer for Multivariate Probabilistic ForecastingContrastive Time Series Forecasting with AnomaliesNaga: Vedic Encoding for Deep State Space ModelsInvDec: Inverted Decoder for Multivariate Time Series Forecasting with Separated Temporal and Variate ModelingQuantum-Optimized Selective State Space Model for Efficient Time Series PredictionAdaMixT: Adaptive Weighted Mixture of Multi-Scale Expert Transformers for Time Series ForecastingReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series ForecastingFATE: Focal-modulated Attention Encoder for Multivariate Time-series ForecastingInstance-wise Graph-based Framework for Multivariate Time Series ForecastingHow Much Can Time-related Features Enhance Time Series Forecasting?Hierarchical Proxy Modeling for Improved HPO in Time Series ForecastingTest Time Learning for Time Series ForecastingTransformer Multivariate Forecasting: Less is More?