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 1351–1375 of 1609 papers

Title	Date	Tasks	Status
PMM-Net: Single-stage Multi-agent Trajectory Prediction with Patching-based Embedding and Explicit Modal Modulation	Oct 25, 2024	Time SeriesTime Series Forecasting	CodeCode Available
Port-Hamiltonian Approach to Neural Network Training	Sep 6, 2019	Time Series Forecasting	CodeCode Available
Better Batch for Deep Probabilistic Time Series Forecasting	May 26, 2023	Decision MakingProbabilistic Time Series Forecasting	CodeCode Available
FDF: Flexible Decoupled Framework for Time Series Forecasting with Conditional Denoising and Polynomial Modeling	Oct 17, 2024	Decision MakingDenoising	CodeCode Available
Powerformer: A Transformer with Weighted Causal Attention for Time-series Forecasting	Feb 10, 2025	Inductive BiasTime Series	CodeCode Available
Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis	Dec 4, 2017	Time SeriesTime Series Analysis	CodeCode Available
Performative Time-Series Forecasting	Oct 9, 2023	Time SeriesTime Series Forecasting	CodeCode Available
Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility	Nov 14, 2019	Time SeriesTime Series Analysis	CodeCode Available
Temporal Attention Augmented Bilinear Network for Financial Time Series Data Analysis	May 5, 2019	Time SeriesTime Series Analysis	CodeCode Available
AverageTime: Enhance Long-Term Time Series Forecasting with Simple Averaging	Dec 30, 2024	Time SeriesTime Series Analysis	CodeCode Available
A New Deep Learning Architecture withInductive Bias Balance for Transformer Oil Temperature Forecasting	May 28, 2023	Inductive BiasTime Series	CodeCode Available
Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm	Jul 7, 2019	GPUTime Series	CodeCode Available
AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting	Dec 20, 2023	AutoMLMeta-Learning	CodeCode Available
Autoregressive Convolutional Recurrent Neural Network for Univariate and Multivariate Time Series Prediction	Mar 6, 2019	Time SeriesTime Series Analysis	CodeCode Available
Predicting Future Mosquito Larval Habitats Using Time Series Climate Forecasting and Deep Learning	Aug 1, 2022	Time SeriesTime Series Analysis	CodeCode Available
Predicting Outcomes in Video Games with Long Short Term Memory Networks	Feb 24, 2024	Decision MakingTime Series	CodeCode Available
Fairness in Forecasting of Observations of Linear Dynamical Systems	Sep 12, 2022	FairnessTime Series	CodeCode Available
AutoFITS: Automatic Feature Engineering for Irregular Time Series	Dec 29, 2021	Feature EngineeringIrregular Time Series	CodeCode Available
Predicting the Number of Reported Bugs in a Software Repository	Apr 24, 2021	Time SeriesTime Series Analysis	CodeCode Available
A Unified Hyperparameter Optimization Pipeline for Transformer-Based Time Series Forecasting Models	Jan 2, 2025	Hyperparameter OptimizationMamba	CodeCode Available
Traffic signal prediction on transportation networks using spatio-temporal correlations on graphs	Apr 27, 2021	Multivariate Time Series ForecastingPrediction	CodeCode Available
Towards Better Forecasting by Fusing Near and Distant Future Visions	Dec 11, 2019	DecoderMultivariate Time Series Forecasting	CodeCode Available
Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy	Jul 13, 2022	Image RegistrationMultivariate Time Series Forecasting	CodeCode Available
PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations	Feb 25, 2024	Multivariate Time Series ForecastingTime Series	CodeCode Available
Predictive Auto-scaling with OpenStack Monasca	Nov 3, 2021	CPUTime Series Analysis	CodeCode Available

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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