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 801–825 of 1609 papers

Title	Date	Tasks	Status
Time-Series Forecasting, Knowledge Distillation, and Refinement within a Multimodal PDE Foundation Model	Sep 17, 2024	Knowledge DistillationOperator learning	CodeCode Available
AALF: Almost Always Linear Forecasting	Sep 16, 2024	Decision MakingDeep Learning	CodeCode Available
Weather Prediction Using CNN-LSTM for Time Series Analysis: A Case Study on Delhi Temperature Data	Sep 14, 2024	energy managementTime Series	—Unverified
Integration of Mamba and Transformer -- MAT for Long-Short Range Time Series Forecasting with Application to Weather Dynamics	Sep 13, 2024	Computational EfficiencyMamba	—Unverified
Automated Data Augmentation for Few-Shot Time Series Forecasting: A Reinforcement Learning Approach Guided by a Model Zoo	Sep 10, 2024	Data AugmentationDiversity	—Unverified
VE: Modeling Multivariate Time Series Correlation with Variate Embedding	Sep 10, 2024	Mixture-of-ExpertsMultivariate Time Series Forecasting	CodeCode Available
Predicting Electricity Consumption with Random Walks on Gaussian Processes	Sep 9, 2024	Decision MakingFew-Shot Learning	—Unverified
A Multi-scenario Attention-based Generative Model for Personalized Blood Pressure Time Series Forecasting	Sep 7, 2024	PrognosisRepresentation Learning	—Unverified
Neural Networks with LSTM and GRU in Modeling Active Fires in the Amazon	Sep 4, 2024	Time SeriesTime Series Forecasting	—Unverified
Boosting Certified Robustness for Time Series Classification with Efficient Self-Ensemble	Sep 4, 2024	Adversarial RobustnessTime Series	—Unverified
Attention-Based Reading, Highlighting, and Forecasting of the Limit Order Book	Sep 3, 2024	Time SeriesTime Series Forecasting	—Unverified
Optimal training of finitely-sampled quantum reservoir computers for forecasting of chaotic dynamics	Sep 2, 2024	DenoisingQuantum Machine Learning	—Unverified
On-device AI: Quantization-aware Training of Transformers in Time-Series	Aug 29, 2024	QuantizationTime Series	—Unverified
DLFormer: Enhancing Explainability in Multivariate Time Series Forecasting using Distributed Lag Embedding	Aug 29, 2024	Multivariate Time Series ForecastingTime Series	—Unverified
Variational Mode Decomposition and Linear Embeddings are What You Need For Time-Series Forecasting	Aug 28, 2024	Time SeriesTime Series Forecasting	CodeCode Available
Adversarial Attacks and Defenses in Multivariate Time-Series Forecasting for Smart and Connected Infrastructures	Aug 27, 2024	Multivariate Time Series ForecastingTime Series	—Unverified
A Multilateral Attention-enhanced Deep Neural Network for Disease Outbreak Forecasting: A Case Study on COVID-19	Aug 26, 2024	Time Series Forecasting	—Unverified
Modeling the Dynamics of Growth in Master-Planned Communities	Aug 26, 2024	NavigateTime Series	CodeCode Available
Language Model Empowered Spatio-Temporal Forecasting via Physics-Aware Reprogramming	Aug 24, 2024	energy managementLanguage Modeling	—Unverified
Geolocation Representation from Large Language Models are Generic Enhancers for Spatio-Temporal Learning	Aug 22, 2024	Spatio-Temporal ForecastingTime Series Forecasting	CodeCode Available
Deconfounding Multi-Cause Latent Confounders: A Factor-Model Approach to Climate Model Bias Correction	Aug 22, 2024	modelTime Series	—Unverified
Simplified Mamba with Disentangled Dependency Encoding for Long-Term Time Series Forecasting	Aug 22, 2024	MambaTime Series	CodeCode Available
Predicting Solar Energy Generation with Machine Learning based on AQI and Weather Features	Aug 22, 2024	Deep LearningPrediction	—Unverified
QuaCK-TSF: Quantum-Classical Kernelized Time Series Forecasting	Aug 21, 2024	Bayesian OptimizationTime Series	CodeCode Available
Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting	Aug 21, 2024	Time SeriesTime Series Forecasting	—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	DLinear	MSE	0.61	—	Unverified
5	MoLE-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	LTBoost (drop_last=false)	MSE	0.33	—	Unverified
10	PRformer	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