Co-occurring keywords · papers mentioning both
Papers
CometNet: Contextual Motif-guided Long-term Time Series Forecasting
AAAI 2026
HMformer: Unleashing Transformer’s Potential for Time Series Forecasting via Hierarchical Multi-Scale Modeling
AAAI 2026
A Lightweight Sparse Interaction Network for Time Series Forecasting
AAAI 2025
Decomposed Spatio-Temporal Mamba for Long-Term Traffic Prediction
AAAI 2025
FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of Experts
AISTATS 2025
HAR-former: Hybrid Transformer with an Adaptive Time-Frequency Representation Matrix for Long-Term Series Forecasting
AISTATS 2025
HyperMixer: Specializable Hypergraph Channel Mixing for Long-term Multivariate Time Series Forecasting
AAAI 2025
Kairos: Redefining Event and Time Prediction with Language Modeling
ACML 2025
Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting
AAAI 2025
WaveletMixer: A Multi-Resolution Wavelets Based MLP-Mixer for Multivariate Long-Term Time Series Forecasting
AAAI 2025
Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
NeurIPS 2024
Are Self-Attentions Effective for Time Series Forecasting?
NeurIPS 2024
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
NeurIPS 2024
DAM: Towards a Foundation Model for Forecasting
ICLR 2024
EasyTS: The Express Lane to Long Time Series Forecasting
AAAI 2024
Mixture-of-Linear-Experts for Long-term Time Series Forecasting
AISTATS 2024
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
NeurIPS 2024
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
ICML 2024
SDformer: Transformer with Spectral Filter and Dynamic Attention for Multivariate Time Series Long-term Forecasting
IJCAI 2024
Self-Supervised Contrastive Learning for Long-term Forecasting
ICLR 2024
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
ICLR 2024
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
ICLR 2023
InParformer: Evolutionary Decomposition Transformers with Interactive Parallel Attention for Long-Term Time Series Forecasting
AAAI 2023
Long-term Wind Power Forecasting with Hierarchical Spatial-Temporal Transformer
IJCAI 2023
SMARTformer: Semi-Autoregressive Transformer with Efficient Integrated Window Attention for Long Time Series Forecasting
IJCAI 2023