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 451500 of 1609 papers

TitleStatusHype
Towards Time Series Reasoning with LLMs0
Implicit Reasoning in Deep Time Series Forecasting0
AALF: Almost Always Linear ForecastingCode0
Weather Prediction Using CNN-LSTM for Time Series Analysis: A Case Study on Delhi Temperature Data0
Integration of Mamba and Transformer -- MAT for Long-Short Range Time Series Forecasting with Application to Weather Dynamics0
Automated Data Augmentation for Few-Shot Time Series Forecasting: A Reinforcement Learning Approach Guided by a Model Zoo0
VE: Modeling Multivariate Time Series Correlation with Variate EmbeddingCode0
Predicting Electricity Consumption with Random Walks on Gaussian Processes0
A Multi-scenario Attention-based Generative Model for Personalized Blood Pressure Time Series Forecasting0
Practical Forecasting of Cryptocoins Timeseries using Correlation PatternsCode1
Boosting Certified Robustness for Time Series Classification with Efficient Self-Ensemble0
Neural Networks with LSTM and GRU in Modeling Active Fires in the Amazon0
Attention-Based Reading, Highlighting, and Forecasting of the Limit Order Book0
Optimal training of finitely-sampled quantum reservoir computers for forecasting of chaotic dynamics0
VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series ForecastersCode3
DLFormer: Enhancing Explainability in Multivariate Time Series Forecasting using Distributed Lag Embedding0
On-device AI: Quantization-aware Training of Transformers in Time-Series0
Variational Mode Decomposition and Linear Embeddings are What You Need For Time-Series ForecastingCode0
Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You NeedCode1
Adversarial Attacks and Defenses in Multivariate Time-Series Forecasting for Smart and Connected Infrastructures0
Modeling the Dynamics of Growth in Master-Planned CommunitiesCode0
A Multilateral Attention-enhanced Deep Neural Network for Disease Outbreak Forecasting: A Case Study on COVID-190
Language Model Empowered Spatio-Temporal Forecasting via Physics-Aware Reprogramming0
DeTPP: Leveraging Object Detection for Robust Long-Horizon Event PredictionCode2
Geolocation Representation from Large Language Models are Generic Enhancers for Spatio-Temporal LearningCode0
An Evaluation of Deep Learning Models for Stock Market Trend PredictionCode1
Deconfounding Multi-Cause Latent Confounders: A Factor-Model Approach to Climate Model Bias Correction0
Simplified Mamba with Disentangled Dependency Encoding for Long-Term Time Series ForecastingCode0
Predicting Solar Energy Generation with Machine Learning based on AQI and Weather Features0
Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting0
QuaCK-TSF: Quantum-Classical Kernelized Time Series ForecastingCode0
KAN4TSF: Are KAN and KAN-based models Effective for Time Series Forecasting?Code2
PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series ForecastingCode2
Wave-Mask/Mix: Exploring Wavelet-Based Augmentations for Time Series ForecastingCode1
Unlocking the Power of LSTM for Long Term Time Series Forecasting0
sTransformer: A Modular Approach for Extracting Inter-Sequential and Temporal Information for Time-Series Forecasting0
Causality-Inspired Models for Financial Time Series Forecasting0
S^3Attention: Improving Long Sequence Attention with Smoothed Skeleton SketchingCode0
Beam Prediction based on Large Language Models0
System States Forecasting of Microservices with Dynamic Spatio-Temporal DataCode0
Local Cold Load Pick-up Estimation Using Customer Energy Consumption Measurements0
Predicting Chaotic System Behavior using Machine Learning Techniques0
An Evaluation of Standard Statistical Models and LLMs on Time Series ForecastingCode0
Anomaly Prediction: A Novel Approach with Explicit Delay and Horizon0
Uncertainty-Aware Crime Prediction With Spatial Temporal Multivariate Graph Neural Networks0
Risk and cross validation in ridge regression with correlated samplesCode1
Scalable Transformer for High Dimensional Multivariate Time Series ForecastingCode1
Early Prediction of Causes (not Effects) in Healthcare by Long-Term Clinical Time Series ForecastingCode0
Inter-Series Transformer: Attending to Products in Time Series Forecasting0
Can LLMs Serve As Time Series Anomaly Detectors?0
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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