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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.
VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting
STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via
AdaPRL: Adaptive Pairwise Regression Learning with Uncertainty Estimation for Universal Regression Tasks
Using Pre-trained LLMs for Multivariate Time Series Forecasting
DCIts -- Deep Convolutional Interpreter for time series
Sensorformer: Cross-patch attention with global-patch compression is effective for high-dimensional multivariate time series forecasting
Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series Prediction
Ister: Inverted Seasonal-Trend Decomposition Transformer for Explainable Multivariate Time Series Forecasting
xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series Analysis
EDformer: Embedded Decomposition Transformer for Interpretable Multivariate Time Series Predictions
DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
Higher Order Transformers: Efficient Attention Mechanism for Tensor Structured Data
Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting
MTS-UNMixers: Multivariate Time Series Forecasting via Channel-Time Dual Unmixing
Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset
LSEAttention is All You Need for Time Series Forecasting
RAM: Replace Attention with MLP for Efficient Multivariate Time Series Forecasting
WaveRoRA: Wavelet Rotary Route Attention for Multivariate Time Series Forecasting
DisenTS: Disentangled Channel Evolving Pattern Modeling for Multivariate Time Series Forecasting
Generative forecasting of brain activity enhances Alzheimer's classification and interpretation
FACTS: A Factored State-Space Framework For World Modelling
xLSTM-Mixer: Multivariate Time Series Forecasting by Mixing via Scalar Memories
LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series Forecasting
UmambaTSF: A U-shaped Multi-Scale Long-Term Time Series Forecasting Method Using Mamba
Less is more: Embracing sparsity and interpolation with Esiformer for time series forecasting
TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting
BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting
TiVaT: A Transformer with a Single Unified Mechanism for Capturing Asynchronous Dependencies in Multivariate Time Series Forecasting
MMFNet: Multi-Scale Frequency Masking Neural Network for Multivariate Time Series Forecasting
MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters
Recurrent Interpolants for Probabilistic Time Series Prediction
VE: Modeling Multivariate Time Series Correlation with Variate Embedding
DLFormer: Enhancing Explainability in Multivariate Time Series Forecasting using Distributed Lag Embedding
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