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

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Showing 601–625 of 1609 papers

Title	Date	Tasks	Status	Score
Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting	May 28, 2025	Time SeriesTime Series Forecasting	CodeCode Available	5
Alternative Telescopic Displacement: An Efficient Multimodal Alignment Method	Jun 29, 2023	Arrhythmia DetectionCross-Modal Retrieval	CodeCode Available	5
Model Compression for Dynamic Forecast Combination	Apr 5, 2021	modelModel Compression	CodeCode Available	5
Modeling the Dynamics of Growth in Master-Planned Communities	Aug 26, 2024	NavigateTime Series	CodeCode Available	5
Correlated daily time series and forecasting in the M4 competition	Mar 28, 2020	Time SeriesTime Series Analysis	CodeCode Available	5
Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model	Mar 30, 2020	Load ForecastingTime Series	CodeCode Available	5
Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers	May 28, 2023	Time SeriesTime Series Forecasting	CodeCode Available	5
Minimal Time Series Transformer	Mar 12, 2025	Time SeriesTime Series Forecasting	CodeCode Available	5
Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators	Apr 1, 2021	Model SelectionTime Series	CodeCode Available	5
Meta-learning and Data Augmentation for Stress Testing Forecasting Models	Jun 24, 2024	Data AugmentationMeta-Learning	CodeCode Available	5
MFRS: A Multi-Frequency Reference Series Approach to Scalable and Accurate Time-Series Forecasting	Mar 11, 2025	Multivariate Time Series ForecastingTime Series	CodeCode Available	5
MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer Recharge	Jul 1, 2024	Model Predictive ControlScheduling	CodeCode Available	5
Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics	Nov 19, 2018	Precipitation ForecastingTime Series Analysis	CodeCode Available	5
Forecasting with Deep Learning: Beyond Average of Average of Average Performance	Jun 24, 2024	Time Series ForecastingUnivariate Time Series Forecasting	CodeCode Available	5
Forecasting time series with constraints	Feb 14, 2025	Additive modelsBenchmarking	CodeCode Available	5
Accurate Uncertainties for Deep Learning Using Calibrated Regression	Jul 1, 2018	Deep LearningModel-based Reinforcement Learning	CodeCode Available	5
MAGMA: Inference and Prediction with Multi-Task Gaussian Processes	Jul 21, 2020	Gaussian ProcessesPrediction	CodeCode Available	5
Forecasting Precipitable Water Vapor Using LSTMs	Jun 26, 2020	Time SeriesTime Series Analysis	CodeCode Available	5
Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters	Sep 29, 2019	BIG-bench Machine LearningTime Series	CodeCode Available	5
Model selection in reconciling hierarchical time series	Oct 21, 2020	modelModel Selection	CodeCode Available	5
Local Attention Mechanism: Boosting the Transformer Architecture for Long-Sequence Time Series Forecasting	Oct 4, 2024	tensor algebraTime Series	CodeCode Available	5
LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting	Dec 9, 2024	Time SeriesTime Series Forecasting	CodeCode Available	5
LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law	Feb 1, 2024	Language ModelingLanguage Modelling	CodeCode Available	5
Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworks	Jun 17, 2025	energy managementTime Series Forecasting	CodeCode Available	5
Conformal time series decomposition with component-wise exchangeability	Jun 24, 2024	Conformal PredictionPrediction	CodeCode Available	5

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All datasets ETTh1 (336) Multivariate ETTh1 (720) Multivariate ETTh2 (336) Multivariate ETTh2 (720) Multivariate ETTh1 (192) Multivariate ETTh2 (192) Multivariate ETTh2 (96) Multivariate ETTh1 (96) Multivariate Weather (192)ETTh1 (720) Univariate Weather (96)Electricity (96)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Informer	MSE	0.88	—	Unverified
2	QuerySelector	MSE	0.85	—	Unverified
3	Transformer	MSE	0.83	—	Unverified
4	Aaren	MSE	0.65	—	Unverified
5	RPMixer	MSE	0.52	—	Unverified
6	MOIRAILarge	MSE	0.51	—	Unverified
7	ATFNet	MSE	0.51	—	Unverified
8	Autoformer	MSE	0.51	—	Unverified
9	SCINet	MSE	0.5	—	Unverified
10	S-Mamba	MSE	0.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	QuerySelector	MSE	1.12	—	Unverified
2	Transformer	MSE	1.11	—	Unverified
3	Informer	MSE	0.94	—	Unverified
4	GLinear	MSE	0.59	—	Unverified
5	SCINet	MSE	0.54	—	Unverified
6	MoLE-DLinear	MSE	0.51	—	Unverified
7	PRformer	MSE	0.49	—	Unverified
8	TEFN	MSE	0.48	—	Unverified
9	DLinear	MSE	0.47	—	Unverified
10	FiLM	MSE	0.47	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Transformer	MSE	2.66	—	Unverified
2	QuerySelector	MSE	2.32	—	Unverified
3	Informer	MSE	1.67	—	Unverified
4	DLinear	MSE	0.45	—	Unverified
5	TEFN	MSE	0.42	—	Unverified
6	MoLE-DLinear	MSE	0.42	—	Unverified
7	FiLM	MSE	0.38	—	Unverified
8	MoLE-RLinear	MSE	0.37	—	Unverified
9	SCINet	MSE	0.37	—	Unverified
10	PRformer	MSE	0.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Transformer	MSE	3.18	—	Unverified
2	QuerySelector	MSE	3.07	—	Unverified
3	Informer	MSE	2.34	—	Unverified
4	MoLE-DLinear	MSE	0.61	—	Unverified
5	DLinear	MSE	0.61	—	Unverified
6	SCINet	MSE	0.48	—	Unverified
7	FiLM	MSE	0.44	—	Unverified
8	TEFN	MSE	0.43	—	Unverified
9	TiDE	MSE	0.42	—	Unverified
10	MoLE-RLinear	MSE	0.41	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MoLE-DLinear	MSE	0.45	—	Unverified
2	TEFN	MSE	0.43	—	Unverified
3	FiLM	MSE	0.41	—	Unverified
4	PatchTST/64	MSE	0.41	—	Unverified
5	TiDE	MSE	0.41	—	Unverified
6	NLinear	MSE	0.41	—	Unverified
7	DiPE-Linear	MSE	0.41	—	Unverified
8	DLinear	MSE	0.41	—	Unverified
9	RLinear	MSE	0.4	—	Unverified
10	MoLE-RLinear	MSE	0.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DLinear	MSE	0.38	—	Unverified
2	TEFN	MSE	0.38	—	Unverified
3	MoLE-DLinear	MSE	0.36	—	Unverified
4	FiLM	MSE	0.36	—	Unverified
5	NLinear	MSE	0.34	—	Unverified
6	PatchTST/64	MSE	0.34	—	Unverified
7	MoLE-RLinear	MSE	0.34	—	Unverified
8	LTBoost (drop_last=false)	MSE	0.33	—	Unverified
9	PRformer	MSE	0.33	—	Unverified
10	TiDE	MSE	0.33	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DLinear	MSE	0.29	—	Unverified
2	TEFN	MSE	0.29	—	Unverified
3	MoLE-DLinear	MSE	0.29	—	Unverified
4	FiLM	MSE	0.28	—	Unverified
5	NLinear	MSE	0.28	—	Unverified
6	TSMixer	MSE	0.28	—	Unverified
7	DiPE-Linear	MSE	0.28	—	Unverified
8	PatchTST/64	MSE	0.27	—	Unverified
9	MoLE-RLinear	MSE	0.27	—	Unverified
10	TiDE	MSE	0.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TEFN	MSE	0.38	—	Unverified
2	MoLE-DLinear	MSE	0.38	—	Unverified
3	MoLE-RLinear	MSE	0.38	—	Unverified
4	TiDE	MSE	0.38	—	Unverified
5	FiLM	MSE	0.37	—	Unverified
6	PatchTST/64	MSE	0.37	—	Unverified
7	DiPE-Linear	MSE	0.37	—	Unverified
8	TSMixer	MSE	0.37	—	Unverified
9	RLinear	MSE	0.37	—	Unverified
10	TTM	MSE	0.36	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TEFN	MSE	0.23	—	Unverified
2	DLinear	MSE	0.22	—	Unverified