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 801850 of 1609 papers

TitleStatusHype
Comparative analysis of financial data differentiation techniques using LSTM neural network0
Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models Evidence from European Financial Markets and Bitcoins0
Comparative analysis of Mixed-Data Sampling (MIDAS) model compared to Lag-Llama model for inflation nowcasting0
Comparative Analysis of Time Series Forecasting Approaches for Household Electricity Consumption Prediction0
Comparative Study of Predicting Stock Index Using Deep Learning Models0
Comparing statistical and machine learning methods for time series forecasting in data-driven logistics -- A simulation study0
Comparison of ARIMA, ETS, NNAR and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy0
Comparison of Traditional and Hybrid Time Series Models for Forecasting COVID-19 Cases0
Conditional Mutual information-based Contrastive Loss for Financial Time Series Forecasting0
Conformalised Conditional Normalising Flows for Joint Prediction Regions in time series0
Construction Cost Index Forecasting: A Multi-feature Fusion Approach0
Construction of neural networks for realization of localized deep learning0
Context Matters: Leveraging Contextual Features for Time Series Forecasting0
Context Neural Networks: A Scalable Multivariate Model for Time Series Forecasting0
Continuous Evolution Pool: Taming Recurring Concept Drift in Online Time Series Forecasting0
Continuous-Time Linear Positional Embedding for Irregular Time Series Forecasting0
ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis0
CoRe: Coherency Regularization for Hierarchical Time Series0
Core Network Management Procedures for Self-Organized and Sustainable 5G Cellular Networks0
Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results0
COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms0
Cross-Frequency Time Series Meta-Forecasting0
Cross-LKTCN: Modern Convolution Utilizing Cross-Variable Dependency for Multivariate Time Series Forecasting Dependency for Multivariate Time Series Forecasting0
Correlation recurrent units: A novel neural architecture for improving the predictive performance of time-series data0
cs-net: structural approach to time-series forecasting for high-dimensional feature space data with limited observations0
Curriculum Learning in Deep Neural Networks for Financial Forecasting0
Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond0
CVTN: Cross Variable and Temporal Integration for Time Series Forecasting0
DAM: Towards A Foundation Model for Time Series Forecasting0
CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting0
DANLIP: Deep Autoregressive Networks for Locally Interpretable Probabilistic Forecasting0
Data Augmentation in Time Series Forecasting through Inverted Framework0
Data Driven Decision Making with Time Series and Spatio-temporal Data0
Data-driven Neural Architecture Learning For Financial Time-series Forecasting0
Data-Driven vs Traditional Approaches to Power Transformer's Top-Oil Temperature Estimation0
DATSING: Data Augmented Time Series Forecasting with Adversarial Domain Adaptation0
Day-ahead time series forecasting: application to capacity planning0
Decentralized Flood Forecasting Using Deep Neural Networks0
Deconfounding Time Series Forecasting0
DeepClair: Utilizing Market Forecasts for Effective Portfolio Selection0
Deep Coupling Network For Multivariate Time Series Forecasting0
Deep Double Descent for Time Series Forecasting: Avoiding Undertrained Models0
Deep Generative Quantile-Copula Models for Probabilistic Forecasting0
DeepHGNN: Study of Graph Neural Network based Forecasting Methods for Hierarchically Related Multivariate Time Series0
Deep Learning for Energy Time-Series Analysis and Forecasting0
Deep Learning for Epidemiological Predictions0
Deep learning for precipitation nowcasting: A survey from the perspective of time series forecasting0
Deep learning for structural health monitoring: An application to heritage structures0
Deep Learning for Time Series Forecasting: A Survey0
Deep Learning in Multiple Multistep Time Series Prediction0
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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