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 11511200 of 1609 papers

TitleStatusHype
S2TX: Cross-Attention Multi-Scale State-Space Transformer for Time Series Forecasting0
Sales forecasting using WaveNet within the framework of the Kaggle competition0
Satellite-based feature extraction and multivariate time-series prediction of biotoxin contamination in shellfish0
Scalable Machine Learning Algorithms using Path Signatures0
Scaling-laws for Large Time-series Models0
SCformer: Segment Correlation Transformer for Long Sequence Time Series Forecasting0
SEED: A Structural Encoder for Embedding-Driven Decoding in Time Series Prediction with LLMs0
Self-Adaptive Forecasting for Improved Deep Learning on Non-Stationary Time-Series0
Self-boosted Time-series Forecasting with Multi-task and Multi-view Learning0
Sensor Response-Time Reduction using Long-Short Term Memory Network Forecasting0
Sentinel: Multi-Patch Transformer with Temporal and Channel Attention for Time Series Forecasting0
Sequence Complementor: Complementing Transformers For Time Series Forecasting with Learnable Sequences0
Sequence to sequence deep learning models for solar irradiation forecasting0
SeriesNet:A Generative Time Series Forecasting Model0
Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting0
Series-to-Series Diffusion Bridge Model0
Short Term Blood Glucose Prediction based on Continuous Glucose Monitoring Data0
Short-term Demand Forecasting for Online Car-hailing Services using Recurrent Neural Networks0
Short-Term Electricity Load Forecasting Using the Temporal Fusion Transformer: Effect of Grid Hierarchies and Data Sources0
Signal Processing over Time-Varying Graphs: A Systematic Review0
Simple Feedfoward Neural Networks are Almost All You Need for Time Series Forecasting0
Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport0
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting0
sktime: A Unified Interface for Machine Learning with Time Series0
SLOTH: Structured Learning and Task-based Optimization for Time Series Forecasting on Hierarchies0
Solar Power Time Series Forecasting Utilising Wavelet Coefficients0
Some variation of COBRA in sequential learning setup0
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting0
Sparsifying Networks via Subdifferential Inclusion0
Spatial-temporal wind field prediction by Artificial Neural Networks0
Spatiotemporal Forecasting in Climate Data Using EOFs and Machine Learning Models: A Case Study in Chile0
Spatiotemporal-Linear: Towards Universal Multivariate Time Series Forecasting0
Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery0
SPAT: Sensitivity-based Multihead-attention Pruning on Time Series Forecasting Models0
Statistical analysis of Wasserstein GANs with applications to time series forecasting0
Stecformer: Spatio-temporal Encoding Cascaded Transformer for Multivariate Long-term Time Series Forecasting0
ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting0
Stochastic Online Convex Optimization. Application to probabilistic time series forecasting0
Stochastic Processes with Modified Lognormal Distribution Featuring Flexible Upper Tail0
Stochastic Recurrent Neural Network for Multistep Time Series Forecasting0
Stock Market Directional Bias Prediction Using ML Algorithms0
Stock Market Telepathy: Graph Neural Networks Predicting the Secret Conversations between MINT and G7 Countries0
Stock Price Forecasting in Presence of Covid-19 Pandemic and Evaluating Performances of Machine Learning Models for Time-Series Forecasting0
sTransformer: A Modular Approach for Extracting Inter-Sequential and Temporal Information for Time-Series Forecasting0
STRGCN: Capturing Asynchronous Spatio-Temporal Dependencies for Irregular Multivariate Time Series Forecasting0
Structural Knowledge Informed Continual Multivariate Time Series Forecasting0
STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via0
Supervised Autoencoder MLP for Financial Time Series Forecasting0
Supervised Autoencoders with Fractionally Differentiated Features and Triple Barrier Labelling Enhance Predictions on Noisy Data0
Surrogate Modeling for Explainable Predictive Time Series Corrections0
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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
4DLinearMSE0.61Unverified
5MoLE-DLinearMSE0.61Unverified
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
8TiDEMSE0.33Unverified
9LTBoost (drop_last=false)MSE0.33Unverified
10PRformerMSE0.33Unverified
#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
3TiDEMSE0.38Unverified
4MoLE-RLinearMSE0.38Unverified
5FiLMMSE0.37Unverified
6PatchTST/64MSE0.37Unverified
7DiPE-LinearMSE0.37Unverified
8TSMixerMSE0.37Unverified
9RLinearMSE0.37Unverified
10TTMMSE0.36Unverified
#ModelMetricClaimedVerifiedStatus
1TEFNMSE0.23Unverified
2DLinearMSE0.22Unverified