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 401450 of 1609 papers

TitleStatusHype
Navigating Inflation in Ghana: How Can Machine Learning Enhance Economic Stability and Growth Strategies0
Less is more: Embracing sparsity and interpolation with Esiformer for time series forecastingCode0
Can LLMs Understand Time Series Anomalies?Code1
Density estimation with LLMs: a geometric investigation of in-context learning trajectories0
Timer-XL: Long-Context Transformers for Unified Time Series ForecastingCode4
TimeCNN: Refining Cross-Variable Interaction on Time Point for Time Series Forecasting0
TimeBridge: Non-Stationarity Matters for Long-term Time Series ForecastingCode2
Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution0
Metadata Matters for Time Series: Informative Forecasting with Transformers0
Local Attention Mechanism: Boosting the Transformer Architecture for Long-Sequence Time Series ForecastingCode0
GAS-Norm: Score-Driven Adaptive Normalization for Non-Stationary Time Series Forecasting in Deep LearningCode0
Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting0
Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs0
Autoregressive Moving-average Attention Mechanism for Time Series ForecastingCode1
Mathematical Formalism for Memory Compression in Selective State Space Models0
Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting0
BACKTIME: Backdoor Attacks on Multivariate Time Series ForecastingCode1
Learning K-U-Net with constant complexity: An Application to time series forecasting0
FAN: Fourier Analysis NetworksCode3
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series ForecastingCode0
MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K ParametersCode3
FredNormer: Frequency Domain Normalization for Non-stationary Time Series Forecasting0
MMFNet: Multi-Scale Frequency Masking Neural Network for Multivariate Time Series ForecastingCode3
TiVaT: A Transformer with a Single Unified Mechanism for Capturing Asynchronous Dependencies in Multivariate Time Series Forecasting0
TSI: A Multi-View Representation Learning Approach for Time Series ForecastingCode0
Frequency Adaptive Normalization For Non-stationary Time Series ForecastingCode2
Continuous-Time Linear Positional Embedding for Irregular Time Series Forecasting0
KODA: A Data-Driven Recursive Model for Time Series Forecasting and Data Assimilation using Koopman Operators0
Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution ShiftsCode1
Optimizing Time Series Forecasting: A Comparative Study of Adam and Nesterov Accelerated Gradient on LSTM and GRU networks Using Stock Market dataCode0
Volatility Forecasting in Global Financial Markets Using TimeMixer0
Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion PerspectiveCode2
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic PatternsCode3
Forecasting Macroeconomic Dynamics using a Calibrated Data-Driven Agent-based Model0
PGN: The RNN's New Successor is Effective for Long-Range Time Series ForecastingCode2
From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with ReflectionCode2
Pre-Finetuning with Impact Duration Awareness for Stock Movement Prediction0
Optimal starting point for time series forecastingCode0
Generative AI-driven forecasting of oil production0
Zero-shot forecasting of chaotic systemsCode4
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of ExpertsCode4
Double-Path Adaptive-correlation Spatial-Temporal Inverted Transformer for Stock Time Series Forecasting0
TSFeatLIME: An Online User Study in Enhancing Explainability in Univariate Time Series ForecastingCode0
TS-HTFA: Advancing Time Series Forecasting via Hierarchical Text-Free Alignment with Large Language Models0
Adaptive Conformal Inference for Multi-Step Ahead Time-Series Forecasting Online0
Test Time Learning for Time Series Forecasting0
ReFine: Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuningCode0
Fine-Tuning a Time Series Foundation Model with Wasserstein LossCode0
Recurrent Interpolants for Probabilistic Time Series Prediction0
Time-Series Forecasting, Knowledge Distillation, and Refinement within a Multimodal PDE Foundation ModelCode0
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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