SOTAVerified

Time Series Forecasting

Time Series Forecasting is the task of fitting a model to historical, time-stamped data in order to predict future values. Traditional approaches include moving average, exponential smoothing, and ARIMA, though models as various as RNNs, Transformers, or XGBoost can also be applied. The most popular benchmark is the ETTh1 dataset. Models are typically evaluated using the Mean Square Error (MSE) or Root Mean Square Error (RMSE).

( Image credit: ThaiBinh Nguyen )

Papers

Showing 251–300 of 1609 papers

TitleStatusHype
PrimeNet: Pre-Training for Irregular Multivariate Time SeriesCode1
Automated Evolutionary Approach for the Design of Composite Machine Learning PipelinesCode1
CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series ForecastingCode1
A Multi-view Multi-task Learning Framework for Multi-variate Time Series ForecastingCode1
KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series ForecastingCode1
K^2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series ForecastingCode1
Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal NarrativeCode1
Large Language Models for Financial Aid in Financial Time-series ForecastingCode1
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series ForecastingCode1
Attractor Memory for Long-Term Time Series Forecasting: A Chaos PerspectiveCode1
Domain Adaptation for Time Series Forecasting via Attention SharingCode1
Interpretable Multivariate Time Series Forecasting with Temporal Attention Convolutional Neural NetworksCode1
Informer: Beyond Efficient Transformer for Long Sequence Time-Series ForecastingCode1
Inductive Graph Neural Networks for Spatiotemporal KrigingCode1
Instance-wise Graph-based Framework for Multivariate Time Series ForecastingCode1
Attention based Multi-Modal New Product Sales Time-series ForecastingCode1
Counterfactual Explanations for Time Series ForecastingCode1
Improved Online Conformal Prediction via Strongly Adaptive Online LearningCode1
Integrating LSTMs and GNNs for COVID-19 ForecastingCode1
Interpretable Multivariate Time Series Forecasting Using Neural Fourier TransformCode1
Attention as an RNNCode1
How Much Can Time-related Features Enhance Time Series Forecasting?Code1
AtsPy: Automated Time Series Forecasting in PythonCode1
Hierarchical Classification Auxiliary Network for Time Series ForecastingCode1
Combating Distribution Shift for Accurate Time Series Forecasting via HypernetworksCode1
Handling Concept Drift in Global Time Series ForecastingCode1
HDT: Hierarchical Discrete Transformer for Multivariate Time Series ForecastingCode1
CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous VariablesCode1
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical ImagesCode1
Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional NetworkCode1
LightCTS: A Lightweight Framework for Correlated Time Series ForecastingCode1
Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic ForecastingCode1
Generative Pretrained Hierarchical Transformer for Time Series ForecastingCode1
Graph-based Time Series Clustering for End-to-End Hierarchical ForecastingCode1
Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated RepresentationsCode1
FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of ExpertsCode1
GBT: Two-stage transformer framework for non-stationary time series forecastingCode1
Graph Neural Controlled Differential Equations for Traffic ForecastingCode1
ForecastPFN: Synthetically-Trained Zero-Shot ForecastingCode1
FrAug: Frequency Domain Augmentation for Time Series ForecastingCode1
An Accurate and Fully-Automated Ensemble Model for Weekly Time Series ForecastingCode1
Forecasting with Hyper-TreesCode1
CondTSF: One-line Plugin of Dataset Condensation for Time Series ForecastingCode1
A Statistics and Deep Learning Hybrid Method for Multivariate Time Series Forecasting and Mortality ModelingCode1
ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series ForecastingCode1
First De-Trend then Attend: Rethinking Attention for Time-Series ForecastingCode1
FlexTSF: A Universal Forecasting Model for Time Series with Variable RegularitiesCode1
Copula Conformal Prediction for Multi-step Time Series ForecastingCode1
Conformal Time-series ForecastingCode1
Financial time series forecasting with multi-modality graph neural networkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InformerMSE0.88—Unverified
2QuerySelectorMSE0.85—Unverified
3TransformerMSE0.83—Unverified
4AarenMSE0.65—Unverified
5RPMixerMSE0.52—Unverified
6ATFNetMSE0.51—Unverified
7MOIRAILargeMSE0.51—Unverified
8AutoformerMSE0.51—Unverified
9SCINetMSE0.5—Unverified
10S-MambaMSE0.49—Unverified
#ModelMetricClaimedVerifiedStatus
1QuerySelectorMSE1.12—Unverified
2TransformerMSE1.11—Unverified
3InformerMSE0.94—Unverified
4GLinearMSE0.59—Unverified
5SCINetMSE0.54—Unverified
6MoLE-DLinearMSE0.51—Unverified
7PRformerMSE0.49—Unverified
8TEFNMSE0.48—Unverified
9DLinearMSE0.47—Unverified
10FiLMMSE0.47—Unverified
#ModelMetricClaimedVerifiedStatus
1TransformerMSE2.66—Unverified
2QuerySelectorMSE2.32—Unverified
3InformerMSE1.67—Unverified
4DLinearMSE0.45—Unverified
5TEFNMSE0.42—Unverified
6MoLE-DLinearMSE0.42—Unverified
7FiLMMSE0.38—Unverified
8MoLE-RLinearMSE0.37—Unverified
9SCINetMSE0.37—Unverified
10PRformerMSE0.36—Unverified
#ModelMetricClaimedVerifiedStatus
1TransformerMSE3.18—Unverified
2QuerySelectorMSE3.07—Unverified
3InformerMSE2.34—Unverified
4MoLE-DLinearMSE0.61—Unverified
5DLinearMSE0.61—Unverified
6SCINetMSE0.48—Unverified
7FiLMMSE0.44—Unverified
8TEFNMSE0.43—Unverified
9TiDEMSE0.42—Unverified
10MoLE-RLinearMSE0.41—Unverified
#ModelMetricClaimedVerifiedStatus
1MoLE-DLinearMSE0.45—Unverified
2TEFNMSE0.43—Unverified
3FiLMMSE0.41—Unverified
4PatchTST/64MSE0.41—Unverified
5TiDEMSE0.41—Unverified
6NLinearMSE0.41—Unverified
7DiPE-LinearMSE0.41—Unverified
8DLinearMSE0.41—Unverified
9RLinearMSE0.4—Unverified
10MoLE-RLinearMSE0.4—Unverified
#ModelMetricClaimedVerifiedStatus
1DLinearMSE0.38—Unverified
2TEFNMSE0.38—Unverified
3MoLE-DLinearMSE0.36—Unverified
4FiLMMSE0.36—Unverified
5NLinearMSE0.34—Unverified
6PatchTST/64MSE0.34—Unverified
7MoLE-RLinearMSE0.34—Unverified
8TiDEMSE0.33—Unverified
9PRformerMSE0.33—Unverified
10LTBoost (drop_last=false)MSE0.33—Unverified
#ModelMetricClaimedVerifiedStatus
1DLinearMSE0.29—Unverified
2TEFNMSE0.29—Unverified
3MoLE-DLinearMSE0.29—Unverified
4FiLMMSE0.28—Unverified
5NLinearMSE0.28—Unverified
6TSMixerMSE0.28—Unverified
7DiPE-LinearMSE0.28—Unverified
8PatchTST/64MSE0.27—Unverified
9MoLE-RLinearMSE0.27—Unverified
10TiDEMSE0.27—Unverified
#ModelMetricClaimedVerifiedStatus
1TEFNMSE0.38—Unverified
2MoLE-DLinearMSE0.38—Unverified
3TiDEMSE0.38—Unverified
4MoLE-RLinearMSE0.38—Unverified
5FiLMMSE0.37—Unverified
6PatchTST/64MSE0.37—Unverified
7DiPE-LinearMSE0.37—Unverified
8TSMixerMSE0.37—Unverified
9RLinearMSE0.37—Unverified
10TTMMSE0.36—Unverified
#ModelMetricClaimedVerifiedStatus
1TEFNMSE0.23—Unverified
2DLinearMSE0.22—Unverified