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 651700 of 1609 papers

TitleStatusHype
A hybrid method of Exponential Smoothing and Recurrent Neural Networks for time series forecastingCode0
A clustering approach to time series forecasting using neural networks: A comparative study on distance-based vs. feature-based clustering methodsCode0
Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal DynamicsCode0
Flow-based Spatio-Temporal Structured Prediction of Motion DynamicsCode0
Flipped Classroom: Effective Teaching for Time Series ForecastingCode0
Asset Price Forecasting using Recurrent Neural NetworksCode0
Meta-learning and Data Augmentation for Stress Testing Forecasting ModelsCode0
Comparison of Deep learning models on time series forecasting : a case study of Dissolved Oxygen PredictionCode0
MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer RechargeCode0
Mitigating Data Redundancy to Revitalize Transformer-based Long-Term Time Series Forecasting SystemCode0
Minimal Time Series TransformerCode0
Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapyCode0
Fine-Tuning a Time Series Foundation Model with Wasserstein LossCode0
Fine-grained Forecasting Models Via Gaussian Process Blurring EffectCode0
Local Attention Mechanism: Boosting the Transformer Architecture for Long-Sequence Time Series ForecastingCode0
LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling lawCode0
LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series ForecastingCode0
Communication-Efficient Design of Learning System for Energy Demand Forecasting of Electrical VehiclesCode0
Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive ForecastingCode0
Leveraging External Factors in Household-Level Electrical Consumption Forecasting using HypernetworksCode0
Less is more: Embracing sparsity and interpolation with Esiformer for time series forecastingCode0
Few-shot human motion prediction for heterogeneous sensorsCode0
Machine Learning vs Statistical Methods for Time Series Forecasting: Size MattersCode0
Combined Dynamic Virtual Spatiotemporal Graph Mapping for Traffic PredictionCode0
Balanced Graph Structure Learning for Multivariate Time Series ForecastingCode0
Feature Fitted Online Conformal Prediction for Deep Time Series Forecasting ModelCode0
Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based PerspectiveCode0
Feature-aligned N-BEATS with Sinkhorn divergenceCode0
FDF: Flexible Decoupled Framework for Time Series Forecasting with Conditional Denoising and Polynomial ModelingCode0
Fast ES-RNN: A GPU Implementation of the ES-RNN AlgorithmCode0
A Capsule Network for Traffic Speed Prediction in Complex Road NetworksCode0
Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit ForecastingCode0
MAGMA: Inference and Prediction with Multi-Task Gaussian ProcessesCode0
Fairness in Forecasting of Observations of Linear Dynamical SystemsCode0
GRATIS: GeneRAting TIme Series with diverse and controllable characteristicsCode0
DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series ForecastingCode0
Lag Selection for Univariate Time Series Forecasting using Deep Learning: An Empirical StudyCode0
Generalization capabilities and robustness of hybrid models grounded in physics compared to purely deep learning modelsCode0
Koopman Ensembles for Probabilistic Time Series ForecastingCode0
Introducing Spectral Attention for Long-Range Dependency in Time Series ForecastingCode0
Explaining deep learning models for ozone pollution prediction via embedded feature selectionCode0
Joint Graph Learning and Model Fitting in Laplacian Regularized Stratified ModelsCode0
Explainable Parallel RCNN with Novel Feature Representation for Time Series ForecastingCode0
Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series ForecastingCode0
Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating SparsityCode0
Experimental study of time series forecasting methods for groundwater level predictionCode0
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series ForecastingCode0
Improving Neural Networks for Time Series Forecasting using Data Augmentation and AutoMLCode0
Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural NetworksCode0
Indeterminate Probability TheoryCode0
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Benchmark Results

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