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 626–650 of 1609 papers

Title	Date	Tasks	Status
Deep Video Prediction for Time Series Forecasting	Feb 24, 2021	Decision MakingPrediction	—Unverified
Analysis of Empirical Mode Decomposition-based Load and Renewable Time Series Forecasting	Nov 23, 2020	Time SeriesTime Series Analysis	—Unverified
Implementing a new fully stepwise decomposition-based sampling technique for the hybrid water level forecasting model in real-world application	Sep 19, 2023	Time SeriesTime Series Forecasting	—Unverified
Implicit Reasoning in Deep Time Series Forecasting	Sep 17, 2024	MemorizationTime Series	—Unverified
Improved Genetic Algorithm Based on Greedy and Simulated Annealing Ideas for Vascular Robot Ordering Strategy	Mar 28, 2024	global-optimizationTime Series	—Unverified
Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition	Dec 30, 2018	Time SeriesTime Series Analysis	—Unverified
In Search of Deep Learning Architectures for Load Forecasting: A Comparative Analysis and the Impact of the Covid-19 Pandemic on Model Performance	Feb 25, 2023	Load ForecastingOut-of-Distribution Generalization	—Unverified
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values	Nov 22, 2019	Missing ValuesMultivariate Time Series Forecasting	—Unverified
Time Series Analysis and Modeling to Forecast: a Survey	Mar 31, 2021	SurveyTime Series	—Unverified
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting	Jun 14, 2024	Hyperparameter OptimizationMulti-Task Learning	—Unverified
Deep State Space Recurrent Neural Networks for Time Series Forecasting	Jul 21, 2024	Kolmogorov-Arnold NetworksState Space Models	—Unverified
Deep State Space Models for Time Series Forecasting	Dec 1, 2018	Deep LearningProbabilistic Time Series Forecasting	—Unverified
AutoPV: Automatically Design Your Photovoltaic Power Forecasting Model	Aug 1, 2024	Neural Architecture SearchTime Series Forecasting	—Unverified
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting	Dec 1, 2020	DecoderTime Series	—Unverified
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems	Jun 3, 2021	DecoderManagement	—Unverified
AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data	Oct 31, 2023	Multivariate Time Series ForecastingTime Series	—Unverified
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting	May 16, 2025	Computational EfficiencyDeep Learning	—Unverified
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	Jun 10, 2021	Demand ForecastingDiversity	—Unverified
Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions	Jan 21, 2025	State Space ModelsStructural Health Monitoring	—Unverified
An Adversarial Learning Approach to Irregular Time-Series Forecasting	Nov 28, 2024	Irregular Time SeriesTime Series	—Unverified
Deep Non-Parametric Time Series Forecaster	Dec 22, 2023	Time SeriesTime Series Forecasting	—Unverified
VLSTM: Very Long Short-Term Memory Networks for High-Frequency Trading	Sep 5, 2018	Time SeriesTime Series Analysis	—Unverified
Automatic Forecasting via Meta-Learning	Sep 29, 2021	Meta-LearningTime Series	—Unverified
HySim: An Efficient Hybrid Similarity Measure for Patch Matching in Image Inpainting	Mar 21, 2024	Image InpaintingPatch Matching	—Unverified
Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL	Jun 15, 2021	Time SeriesTime Series Analysis	—Unverified

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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