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 201250 of 1609 papers

TitleStatusHype
CARD: Channel Aligned Robust Blend Transformer for Time Series ForecastingCode1
Embedded feature selection in LSTM networks with multi-objective evolutionary ensemble learning for time series forecastingCode1
Battling the Non-stationarity in Time Series Forecasting via Test-time AdaptationCode1
Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series ForecastingCode1
BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable BasisCode1
A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy PerspectiveCode1
Bellman Conformal Inference: Calibrating Prediction Intervals For Time SeriesCode1
A Comprehensive Survey of Regression Based Loss Functions for Time Series ForecastingCode1
BACKTIME: Backdoor Attacks on Multivariate Time Series ForecastingCode1
An Analysis of Linear Time Series Forecasting ModelsCode1
An Evaluation of Deep Learning Models for Stock Market Trend PredictionCode1
Ensembles of Localised Models for Time Series ForecastingCode1
Enhancing Battery Storage Energy Arbitrage with Deep Reinforcement Learning and Time-Series ForecastingCode1
Ensemble Conformalized Quantile Regression for Probabilistic Time Series ForecastingCode1
TS2Vec: Towards Universal Representation of Time SeriesCode1
Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series ForecastingCode1
Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution ShiftsCode1
LLM-Mixer: Multiscale Mixing in LLMs for Time Series ForecastingCode1
Learning Fast and Slow for Online Time Series ForecastingCode1
Learning Gaussian Mixture Representations for Tensor Time Series ForecastingCode1
EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction taskCode1
Long-term series forecasting with Query Selector -- efficient model of sparse attentionCode1
LaT-PFN: A Joint Embedding Predictive Architecture for In-context Time-series ForecastingCode1
auto-sktime: Automated Time Series ForecastingCode1
A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint PredictionCode1
FAITH: Frequency-domain Attention In Two Horizons for Time Series ForecastingCode1
Dynamic Graph Learning-Neural Network for Multivariate Time Series ModelingCode1
Expressing Multivariate Time Series as Graphs with Time Series Attention TransformerCode1
An Experimental Review on Deep Learning Architectures for Time Series ForecastingCode1
FCDNet: Frequency-Guided Complementary Dependency Modeling for Multivariate Time-Series ForecastingCode1
Autoregressive Moving-average Attention Mechanism for Time Series ForecastingCode1
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series ForecastingCode1
MemDA: Forecasting Urban Time Series with Memory-based Drift AdaptationCode1
Unlocking the Potential of Deep Learning in Peak-Hour Series ForecastingCode1
Adversarial Sparse Transformer for Time Series ForecastingCode1
Few-Shot Forecasting of Time-Series with Heterogeneous ChannelsCode1
Learning to Embed Time Series Patches IndependentlyCode1
Federated Learning for 5G Base Station Traffic ForecastingCode1
D-PAD: Deep-Shallow Multi-Frequency Patterns Disentangling for Time Series ForecastingCode1
Adversarial Vulnerabilities in Large Language Models for Time Series ForecastingCode1
An Open Source and Reproducible Implementation of LSTM and GRU Networks for Time Series ForecastingCode1
KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series ForecastingCode1
Do We Really Need Deep Learning Models for Time Series Forecasting?Code1
Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative RegularizationCode1
DiTEC-WDN: A Large-Scale Dataset of Hydraulic Scenarios across Multiple Water Distribution NetworksCode1
Financial time series forecasting with multi-modality graph neural networkCode1
Time series forecasting with Gaussian Processes needs priorsCode1
Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series ForecastingCode1
Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across CitiesCode1
K^2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series ForecastingCode1
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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