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 226–250 of 1609 papers

Title	Date	Tasks	Status	Hype	Score
EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task	Apr 16, 2021	Crop Yield PredictionEarth Surface Forecasting	CodeCode Available	1	5
Autoregressive Moving-average Attention Mechanism for Time Series Forecasting	Oct 4, 2024	DecoderTime Series	CodeCode Available	1	5
FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time Series Forecasting	Jun 19, 2023	Inductive BiasTime Series	CodeCode Available	1	5
An Experimental Review on Deep Learning Architectures for Time Series Forecasting	Mar 22, 2021	Deep LearningTime Series	CodeCode Available	1	5
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting	Jul 30, 2020	ManagementTime Series	CodeCode Available	1	5
Learning Gaussian Mixture Representations for Tensor Time Series Forecasting	Jun 1, 2023	Representation LearningTime Series	CodeCode Available	1	5
Learning to Embed Time Series Patches Independently	Dec 27, 2023	Contrastive LearningRepresentation Learning	CodeCode Available	1	5
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting	May 20, 2023	Time SeriesTime Series Forecasting	CodeCode Available	1	5
Unlocking the Potential of Deep Learning in Peak-Hour Series Forecasting	Jul 4, 2023	DecoderTime Series	CodeCode Available	1	5
Adversarial Sparse Transformer for Time Series Forecasting	Dec 1, 2020	Multivariate Time Series ForecastingPrediction	CodeCode Available	1	5
Federated Learning for 5G Base Station Traffic Forecasting	Nov 28, 2022	Federated LearningManagement	CodeCode Available	1	5
Few-Shot Forecasting of Time-Series with Heterogeneous Channels	Apr 7, 2022	ClassificationTime Series	CodeCode Available	1	5
Meta-learning framework with applications to zero-shot time-series forecasting	Feb 7, 2020	Meta-LearningTime Series	CodeCode Available	1	5
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors	Sep 9, 2019	Object LocalizationPrediction	CodeCode Available	1	5
Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting	Dec 11, 2024	Adversarial AttackTime Series	CodeCode Available	1	5
An Open Source and Reproducible Implementation of LSTM and GRU Networks for Time Series Forecasting	Jun 22, 2022	Time SeriesTime Series Analysis	CodeCode Available	1	5
KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series Forecasting	Jun 10, 2025	Computational EfficiencyMamba	CodeCode Available	1	5
D-PAD: Deep-Shallow Multi-Frequency Patterns Disentangling for Time Series Forecasting	Mar 26, 2024	Time SeriesTime Series Forecasting	CodeCode Available	1	5
Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization	Jun 29, 2024	Dynamic Time WarpingPrediction	CodeCode Available	1	5
K^2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting	May 29, 2025	Decision MakingProbabilistic Time Series Forecasting	CodeCode Available	1	5
Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities	Feb 8, 2022	Domain AdaptationGraph Mining	CodeCode Available	1	5
DiTEC-WDN: A Large-Scale Dataset of Hydraulic Scenarios across Multiple Water Distribution Networks	Mar 21, 2025	Time Series Forecasting	CodeCode Available	1	5
Do We Really Need Deep Learning Models for Time Series Forecasting?	Jan 6, 2021	Deep Learningregression	CodeCode Available	1	5
Time series forecasting with Gaussian Processes needs priors	Sep 17, 2020	Gaussian ProcessesTime Series	CodeCode Available	1	5
Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network	Aug 31, 2023	Time SeriesTime Series Forecasting	CodeCode Available	1	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