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 151–200 of 1609 papers

TitleStatusHype
Probabilistic Time Series Forecasting with Implicit Quantile NetworksCode2
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series ForecastingCode2
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series ForecastingCode2
Deep Learning for Time Series Forecasting: Tutorial and Literature SurveyCode2
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing FlowsCode2
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series ForecastingCode2
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent NetworksCode2
A foundation model with multi-variate parallel attention to generate neuronal activityCode1
PeakWeather: MeteoSwiss Weather Station Measurements for Spatiotemporal Deep LearningCode1
KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series ForecastingCode1
LETS Forecast: Learning Embedology for Time Series ForecastingCode1
Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series ForecastingCode1
Timing is Important: Risk-aware Fund Allocation based on Time-Series ForecastingCode1
K^2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series ForecastingCode1
CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous VariablesCode1
CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial CorrelationsCode1
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series ForecastingCode1
Sonnet: Spectral Operator Neural Network for Multivariable Time Series ForecastingCode1
Time series saliency maps: explaining models across multiple domainsCode1
Non-Stationary Time Series Forecasting Based on Fourier Analysis and Cross Attention MechanismCode1
FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series ForecastingCode1
Retrieval Augmented Time Series ForecastingCode1
CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series ForecastingCode1
Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated RepresentationsCode1
TSRM: A Lightweight Temporal Feature Encoding Architecture for Time Series Forecasting and ImputationCode1
TimeCapsule: Solving the Jigsaw Puzzle of Long-Term Time Series Forecasting with Compressed Predictive RepresentationsCode1
Enhancing Time Series Forecasting via Multi-Level Text Alignment with LLMsCode1
Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series ForecastingCode1
DiTEC-WDN: A Large-Scale Dataset of Hydraulic Scenarios across Multiple Water Distribution NetworksCode1
MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question AnsweringCode1
Mamba time series forecasting with uncertainty quantificationCode1
Small but Mighty: Enhancing Time Series Forecasting with Lightweight LLMsCode1
SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series ForecastingCode1
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion ModelsCode1
ReFocus: Reinforcing Mid-Frequency and Key-Frequency Modeling for Multivariate Time Series ForecastingCode1
TimePFN: Effective Multivariate Time Series Forecasting with Synthetic DataCode1
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series ForecastingCode1
A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy PerspectiveCode1
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series ForecastingCode1
Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal NarrativeCode1
HDT: Hierarchical Discrete Transformer for Multivariate Time Series ForecastingCode1
SWIFT: Mapping Sub-series with Wavelet Decomposition Improves Time Series ForecastingCode1
FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of ExpertsCode1
VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series ForecastingCode1
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series ForecastingCode1
SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM TrainingCode1
Battling the Non-stationarity in Time Series Forecasting via Test-time AdaptationCode1
Neural Conformal Control for Time Series ForecastingCode1
TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series AnalysisCode1
Adversarial Vulnerabilities in Large Language Models for Time Series ForecastingCode1
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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