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 701–725 of 1609 papers

Title	Date	Tasks	Status	Hype
Predicting Outcomes in Video Games with Long Short Term Memory Networks	Feb 24, 2024	Decision MakingTime Series	CodeCode Available	0
Deep Coupling Network For Multivariate Time Series Forecasting	Feb 23, 2024	Multivariate Time Series ForecastingTime Series	—Unverified	0
Adaptive time series forecasting with markovian variance switching	Feb 22, 2024	Learning TheoryLoad Forecasting	—Unverified	0
DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging Load	Feb 21, 2024	DenoisingLoad Forecasting	CodeCode Available	1
Generative Probabilistic Time Series Forecasting and Applications in Grid Operations	Feb 21, 2024	Decision MakingProbabilistic Time Series Forecasting	—Unverified	0
Structural Knowledge Informed Continual Multivariate Time Series Forecasting	Feb 20, 2024	Continual LearningGraph structure learning	—Unverified	0
When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting	Feb 20, 2024	Time SeriesTime Series Forecasting	—Unverified	0
Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling	Feb 20, 2024	Multivariate Time Series ForecastingTime Series	CodeCode Available	2
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective	Feb 18, 2024	Time SeriesTime Series Forecasting	CodeCode Available	1
RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data	Feb 16, 2024	AllDiversity	—Unverified	0
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities	Feb 16, 2024	Time SeriesTime Series Forecasting	CodeCode Available	1
Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review	Feb 15, 2024	Anomaly ClassificationAnomaly Detection	—Unverified	0
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention	Feb 15, 2024	Time SeriesTime Series Forecasting	CodeCode Available	2
Loss Shaping Constraints for Long-Term Time Series Forecasting	Feb 14, 2024	Time SeriesTime Series Forecasting	—Unverified	0
Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction	Feb 12, 2024	Multivariate Time Series ForecastingTime Series	—Unverified	0
Attention as Robust Representation for Time Series Forecasting	Feb 8, 2024	Multivariate Time Series ForecastingTime Series	—Unverified	0
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting	Feb 8, 2024	Computational EfficiencyMultivariate Time Series Forecasting	—Unverified	0
Bellman Conformal Inference: Calibrating Prediction Intervals For Time Series	Feb 7, 2024	Prediction IntervalsTime Series	CodeCode Available	1
Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning	Feb 7, 2024	Contrastive LearningPrediction	CodeCode Available	2
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting	Feb 4, 2024	Time SeriesTime Series Forecasting	CodeCode Available	3
Timer: Generative Pre-trained Transformers Are Large Time Series Models	Feb 4, 2024	Anomaly DetectionImputation	CodeCode Available	4
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models	Feb 4, 2024	DecoderIn-Context Learning	CodeCode Available	3
Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals	Feb 4, 2024	Ensemble LearningTime Series	CodeCode Available	2
Unified Training of Universal Time Series Forecasting Transformers	Feb 4, 2024	Time SeriesTime Series Forecasting	CodeCode Available	5
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies	Feb 3, 2024	Time SeriesTime Series Forecasting	CodeCode Available	1

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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