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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–125 of 1609 papers

Title	Date	Tasks	Status	Hype
Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges	Apr 24, 2024	Drug DesignInductive Bias	CodeCode Available	2
An End-to-End Structure with Novel Position Mechanism and Improved EMD for Stock Forecasting	Mar 25, 2024	PositionTime Series	CodeCode Available	2
PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting	Sep 26, 2024	Time SeriesTime Series Forecasting	CodeCode Available	2
Learning Deep Time-index Models for Time Series Forecasting	Jul 13, 2022	Inductive BiasMeta-Learning	CodeCode Available	2
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting	Jul 21, 2023	ImputationProbabilistic Time Series Forecasting	CodeCode Available	2
Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting	Jun 18, 2022	Graph Neural NetworkMultivariate Time Series Forecasting	CodeCode Available	2
Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals	Feb 4, 2024	Ensemble LearningTime Series	CodeCode Available	2
DeTPP: Leveraging Object Detection for Robust Long-Horizon Event Prediction	Aug 23, 2024	DiversityPoint Processes	CodeCode Available	2
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons	Oct 11, 2023	BenchmarkingPosition	CodeCode Available	2
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series	May 30, 2023	Anomaly DetectionClassification	CodeCode Available	2
Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning	Feb 7, 2024	Contrastive LearningPrediction	CodeCode Available	2
Model scale versus domain knowledge in statistical forecasting of chaotic systems	Mar 13, 2023	Time SeriesTime Series Analysis	CodeCode Available	2
Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift	Oct 13, 2024	Time SeriesTime Series Forecasting	CodeCode Available	2
RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks	Jan 17, 2024	Computational EfficiencyTime Series	CodeCode Available	2
Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting	Oct 31, 2024	Time SeriesTime Series Forecasting	CodeCode Available	2
Self-Supervised Contrastive Learning for Long-term Forecasting	Feb 3, 2024	Contrastive LearningTime Series	CodeCode Available	2
Large Language Models Are Zero-Shot Time Series Forecasters	Oct 11, 2023	ImputationTime Series	CodeCode Available	2
Large language models can be zero-shot anomaly detectors for time series?	May 23, 2024	Anomaly DetectionLanguage Modeling	CodeCode Available	2
LibCity: An Open Library for Traffic Prediction	Nov 4, 2021	Multivariate Time Series ForecastingPrediction	CodeCode Available	2
HoTPP Benchmark: Are We Good at the Long Horizon Events Forecasting?	Jun 20, 2024	BenchmarkingPoint Processes	CodeCode Available	2
KAN4TSF: Are KAN and KAN-based models Effective for Time Series Forecasting?	Aug 21, 2024	Mixture-of-ExpertsTime Series	CodeCode Available	2
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows	Feb 14, 2020	Decision MakingMultivariate Time Series Forecasting	CodeCode Available	2
Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement	Jan 8, 2023	DenoisingDisentanglement	CodeCode Available	2
GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing	May 18, 2024	Multivariate Time Series ForecastingTime Series	CodeCode Available	2
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting	Nov 10, 2023	Time SeriesTime Series Forecasting	CodeCode Available	2

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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	ATFNet	MSE	0.51	—	Unverified
7	MOIRAILarge	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	TiDE	MSE	0.33	—	Unverified
9	PRformer	MSE	0.33	—	Unverified
10	LTBoost (drop_last=false)	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	TiDE	MSE	0.38	—	Unverified
4	MoLE-RLinear	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