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Multivariate Time Series Forecasting
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting
Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
Kernel-U-Net: Multivariate Time Series Forecasting using Custom Kernels
MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting
FCDNet: Frequency-Guided Complementary Dependency Modeling for Multivariate Time-Series Forecasting
Spatiotemporal-Linear: Towards Universal Multivariate Time Series Forecasting
CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting
Sparse Transformer with Local and Seasonal Adaptation for Multivariate Time Series Forecasting
Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach
Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting
TimeSQL: Improving Multivariate Time Series Forecasting with Multi-Scale Patching and Smooth Quadratic Loss
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective
AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data
Pyramidal Hidden Markov Model For Multivariate Time Series Forecasting
UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
Revealing the Power of Masked Autoencoders in Traffic Forecasting
MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation
Multi-scale Transformer Pyramid Networks for Multivariate Time Series Forecasting
LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters
PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer
SageFormer: Series-Aware Framework for Long-term Multivariate Time Series Forecasting
Improving the Transferability of Time Series Forecasting with Decomposition Adaptation
Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting
GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting
Cross-LKTCN: Modern Convolution Utilizing Cross-Variable Dependency for Multivariate Time Series Forecasting Dependency for Multivariate Time Series Forecasting
A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecasting
Forecasting Irregularly Sampled Time Series using Graphs
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting
The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting
Indeterminate Probability Theory
LightCTS: A Lightweight Framework for Correlated Time Series Forecasting
SLOTH: Structured Learning and Task-based Optimization for Time Series Forecasting on Hierarchies
MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing
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