Awesome Time Series Forecasting/Prediction Papers

This repository contains a reading list of papers (300+ papers !!!) on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model. This repository is still being continuously improved. In addition to papers that have been accepted by top conferences or journals, the repository also includes the latest papers from arXiv. If you have found any relevant papers that need to be included in this repository, please feel free to submit a pull request (PR) or open an issue. If you find this repository useful, please give it a 🌟.

Each paper may apply to one or several types of forecasting, including univariate time series forecasting, multivariate time series forecasting, and spatio-temporal forecasting, which are also marked in the Type column. If covariates and exogenous variables are not considered, univariate time series forecasting involves predicting the future of one variable with the history of this variable, while multivariate time series forecasting involves predicting the future of C variables with the history of C variables. Note that repeating univariate forecasting multiple times can also achieve the goal of multivariate forecasting, which is called channel-independent. However, univariate forecasting methods cannot extract relationships between variables, so the basis for distinguishing between univariate and multivariate forecasting methods is whether the method involves interaction between variables. Besides, in the era of deep learning, many univariate models can be easily modified to directly process multiple variables for multivariate forecasting. And multivariate models generally can be directly used for univariate forecasting. Here we classify solely based on the model's description in the original paper. Spatio-temporal forecasting is often used in traffic and weather forecasting, and it adds a spatial dimension compared to univariate and multivariate forecasting. In spatio-temporal forecasting, if each measurement point has only one variable, it is equivalent to multivariate forecasting. Therefore, the distinction between spatio-temporal forecasting and multivariate forecasting is not clear. Spatio-temporal models can usually be directly applied to multivariate forecasting, and multivariate models can also be used for spatio-temporal forecasting with minor modifications. Here we also classify solely based on the model's description in the original paper.

• univariate time series forecasting: , where L is the history length, H is the prediction horizon length.
• multivariate time series forecasting: , where C is the number of variables (channels).
• spatio-temporal forecasting: , where N is the spatial dimension (number of measurement points).
• irregular time series: observation/sampling times are irregular.

Some Additional Information.

🚩 2023/11/1: I have marked some recommended papers with 🌟 (Just my personal preference 😉).

🚩 2023/11/1: I have added a new category : models specifically designed for irregular time series.

🚩 2023/11/1: I also recommend you to check out some other GitHub repositories about awesome time series papers: time-series-transformers-review, awesome-AI-for-time-series-papers, time-series-papers, deep-learning-time-series.

🚩 2023/11/3: There are some popular toolkits or code libraries that integrate many time series models: Time-Series-Library, Prophet, Darts, Kats, tsai, GluonTS, PyTorchForecasting, tslearn, AutoGluon, flow-forecast, PyFlux.

🚩 2023/12/28: Since the topic of LLM(Large Language Model)+TS(Time Series) has been popular recently, I have introduced a category (LLM) to include related papers. This is distinguished from the Pretrain category. Pretrain mainly contains papers which design agent tasks (contrastive or generative) suitable for time series, and only use large-scale time series data for pre-training.

🚩 2024/4/1: Some researchers have introduced the recently popular Mamba model into the field of time series forecasting, which can be found in the SSM (State Space Model) table.

🚩 2024/6/7: I will mark some hot papers with 🔥 (Papers with over 100 citations).

Survey & Benchmark.

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
15-11-23	Multi-step	ACOMP 2015	Comparison of Strategies for Multi-step-Ahead Prediction of Time Series Using Neural Network	None
19-06-20	DL🔥	SENSJ 2019	A Review of Deep Learning Models for Time Series Prediction	None
20-09-27	DL🔥	Arxiv 2020	Time Series Forecasting With Deep Learning: A Survey	None
22-02-15	Transformer🔥	IJCAI 2023	Transformers in Time Series: A Survey	PaperList
23-03-25	STGNN🔥	TKDE 2023	Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey	None
23-05-01	Diffusion	Arxiv 2023	Diffusion Models for Time Series Applications: A Survey	None
23-06-16	SSL	TPAMI 2024	Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects	None
23-06-20	OpenSTL	NIPS 2023	OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning	Benchmark
23-07-07	GNN	Arxiv 2023	A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection	PaperList
23-10-09	BasicTS	Arxiv 2023	Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis	Benchmark
23-10-11	ProbTS	Arxiv 2023	ProbTS: A Unified Toolkit to Probe Deep Time-series Forecasting	Toolkit
23-12-28	TSPP	Arxiv 2023	TSPP: A Unified Benchmarking Tool for Time-series Forecasting	TSPP
24-01-05	Diffusion	Arxiv 2024	The Rise of Diffusion Models in Time-Series Forecasting	None
24-02-15	LLM	Arxiv 2024	Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review	None
24-03-21	FM	Arxiv 2024	Foundation Models for Time Series Analysis: A Tutorial and Survey	None
24-03-29	TFB	VLDB 2024	TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods	TFB
24-04-24	Mamba-360	Arxiv 2024	Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges	Mamba-360
24-04-29	Diffusion	Arxiv 2024	A Survey on Diffusion Models for Time Series and Spatio-Temporal Data	PaperList
24-05-03	FoundationModels	Arxiv 2024	A Survey of Time Series Foundation Models: Generalizing Time Series Representation with Large Language Model	PaperList

Transformer.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
19-06-29	LogTrans🔥		NIPS 2019	Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting	flowforecast
19-12-19	TFT🌟🔥		IJoF 2021	Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting	tft
20-01-23	InfluTrans🔥		Arxiv 2020	Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case	influenza transformer
20-06-05	AST 🔥		NIPS 2020	Adversarial Sparse Transformer for Time Series Forecasting	AST
20-12-14	Informer🌟🔥		AAAI 2021	Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting	Informer
21-05-22	ProTran		NIPS 2021	Probabilistic Transformer for Time Series Analysis	None
21-06-24	Autoformer🌟🔥		NIPS 2021	Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting	Autoformer
21-09-17	Aliformer		Arxiv 2021	From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba	None
21-10-05	Pyraformer🔥		ICLR 2022	Pyraformer: Low-complexity Pyramidal Attention for Long-range Time Series Modeling and Forecasting	Pyraformer
22-01-14	Preformer		ICASSP 2023	Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series Forecasting	Preformer
22-01-30	FEDformer🌟🔥		ICML 2022	FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting	FEDformer
22-02-03	ETSformer		Arxiv 2022	ETSformer: Exponential Smoothing Transformers for Time-series Forecasting	etsformer
22-02-07	TACTiS		ICML 2022	TACTiS: Transformer-Attentional Copulas for Time Series	TACTiS
22-04-28	Triformer		IJCAI 2022	Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting	Triformer
22-05-27	TDformer		NIPSW 2022	First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting	TDformer
22-05-28	Non-stationary Transformer		NIPS 2022	Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting	Non-stationary Transformers
22-06-08	Scaleformer		ICLR 2023	Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting	Scaleformer
22-08-14	Quatformer		KDD 2022	Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting	Quatformer
22-08-30	Persistence Initialization		Arxiv 2022	Persistence Initialization: A novel adaptation of the Transformer architecture for Time Series Forecasting	None
22-09-08	W-Transformers		Arxiv 2022	W-Transformers: A Wavelet-based Transformer Framework for Univariate Time Series Forecasting	w-transformer
22-09-22	Crossformer		ICLR 2023	Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting	Crossformer
22-09-22	PatchTST🌟		ICLR 2023	A Time Series is Worth 64 Words: Long-term Forecasting with Transformers	PatchTST
22-11-29	AirFormer		AAAI 2023	AirFormer: Predicting Nationwide Air Quality in China with Transformers	AirFormer
22-12-06	TVT		Arxiv 2022	A K-variate Time Series Is Worth K Words: Evolution of the Vanilla Transformer Architecture for Long-term Multivariate Time Series Forecasting	None
23-01-05	Conformer		ICDE 2023	Towards Long-Term Time-Series Forecasting: Feature, Pattern, and Distribution	Conformer
23-01-19	PDFormer		AAAI 2023	PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction	PDFormer
23-03-01	ViTST		NIPS 2023	Time Series as Images: Vision Transformer for Irregularly Sampled Time Series	ViTST
23-05-20	CARD		ICLR 2024	Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer	CARD
23-05-24	JTFT		Arxiv 2023	A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecasting	None
23-05-30	HSTTN		IJCAI 2023	Long-term Wind Power Forecasting with Hierarchical Spatial-Temporal Transformer	None
23-05-30	Client		Arxiv 2023	Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting	Client
23-05-30	Taylorformer		Arxiv 2023	Taylorformer: Probabilistic Predictions for Time Series and other Processes	Taylorformer
23-06-05	Corrformer🌟		NMI 2023	Interpretable weather forecasting for worldwide stations with a unified deep model	Corrformer
23-06-14	GCformer		CIKM 2023	GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting	GCformer
23-07-04	SageFormer		IoT 2024	SageFormer: Series-Aware Graph-Enhanced Transformers for Multivariate Time Series Forecasting	SageFormer
23-07-10	DifFormer		TPAMI 2023	DifFormer: Multi-Resolutional Differencing Transformer With Dynamic Ranging for Time Series Analysis	None
23-07-27	HUTFormer		Arxiv 2023	HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting	None
23-08-07	DSformer		CIKM 2023	DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction	None
23-08-09	SBT		KDD 2023	Sparse Binary Transformers for Multivariate Time Series Modeling	None
23-08-09	PETformer		Arxiv 2023	PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer	None
23-10-02	TACTiS-2		ICLR 2024	TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series	None
23-10-03	PrACTiS		Arxiv 2023	PrACTiS: Perceiver-Attentional Copulas for Time Series	None
23-10-10	iTransformer		ICLR 2024	iTransformer: Inverted Transformers Are Effective for Time Series Forecasting	iTransformer
23-10-26	ContiFormer		NIPS 2023	ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling	None
23-10-31	BasisFormer		NIPS 2023	BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis	basisformer
23-11-07	MTST		Arxiv 2023	Multi-resolution Time-Series Transformer for Long-term Forecasting	None
23-11-30	MultiResFormer		Arxiv 2023	MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting	None
23-12-10	FPPformer		IOT 2023	Take an Irregular Route: Enhance the Decoder of Time-Series Forecasting Transformer	FPPformer
23-12-11	Dozerformer		Arxiv 2023	Dozerformer: Sequence Adaptive Sparse Transformer for Multivariate Time Series Forecasting	None
23-12-11	CSformer		Arxiv 2023	Dance of Channel and Sequence: An Efficient Attention-Based Approach for Multivariate Time Series Forecasting	None
23-12-23	MASTER		AAAI 2024	MASTER: Market-Guided Stock Transformer for Stock Price Forecasting	MASTER
23-12-30	PCA+former		Arxiv 2023	Transformer Multivariate Forecasting: Less is More?	None
24-01-16	PDF		ICLR 2024	Periodicity Decoupling Framework for Long-term Series Forecasting	PDF
24-01-16	Pathformer		ICLR 2024	Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting	None
24-01-16	VQ-TR		ICLR 2024	VQ-TR: Vector Quantized Attention for Time Series Forecasting	None
24-01-22	HDformer		Arxiv 2024	The Bigger the Better? Rethinking the Effective Model Scale in Long-term Time Series Forecasting	None
24-02-04	Minusformer		Arxiv 2024	Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals	Minusformer
24-02-08	AttnEmbed		Arxiv 2024	Attention as Robust Representation for Time Series Forecasting	AttnEmbed
24-02-15	SAMformer		ICML 2024	Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention	SAMformer
24-02-25	PDETime		Arxiv 2024	PDETime: Rethinking Long-Term Multivariate Time Series Forecasting from the perspective of partial differential equations	None
24-02-29	TimeXer		Arxiv 2024	TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables	None
24-03-05	InjectTST		Arxiv 2024	InjectTST: A Transformer Method of Injecting Global Information into Independent Channels for Long Time Series Forecasting	None
24-03-13	Caformer		Arxiv 2024	Caformer: Rethinking Time Series Analysis from Causal Perspective	None
24-03-14	MCformer		Arxiv 2024	MCformer: Multivariate Time Series Forecasting with Mixed-Channels Transformer	None
24-04-08	ATFNet		Arxiv 2024	ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecasting	ATFNet
24-04-12	TSLANet		ICML 2024	TSLANet: Rethinking Transformers for Time Series Representation Learning	TSLANet
24-04-16	T2B-PE		Arxiv 2024	Intriguing Properties of Positional Encoding in Time Series Forecasting	T2B-PE
24-05-14	DGCformer		Arxiv 2024	DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecasting	None
24-05-19	VCformer		Arxiv 2024	VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting	VCformer
24-05-22	GridTST		Arxiv 2024	Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla Transformers	GridTST
24-05-23	ICTSP		Arxiv 2024	In-context Time Series Predictor	None
24-05-27	CATS		Arxiv 2024	Are Self-Attentions Effective for Time Series Forecasting?	None
24-06-06	TwinS		Arxiv 2024	TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecasting	None
24-06-07	UniTST		Arxiv 2024	UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting	None
24-06-11	DeformTime		Arxiv 2024	DeformTime: Capturing Variable Dependencies with Deformable Attention for Time Series Forecasting	DeformTime
24-06-13	Fredformer		KDD 2024	Fredformer: Frequency Debiased Transformer for Time Series Forecasting	Fredformer

RNN.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
17-03-21	LSTNet🌟		SIGIR 2018	Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks	LSTNet
17-04-07	DA-RNN		IJCAI 2017	A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction	DARNN
17-04-13	DeepAR🌟		IJoF 2019	DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks	DeepAR
17-11-29	MQRNN		NIPSW 2017	A Multi-Horizon Quantile Recurrent Forecaster	MQRNN
18-06-23	mWDN		KDD 2018	Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis	mWDN
18-09-06	MTNet		AAAI 2019	A Memory-Network Based Solution for Multivariate Time-Series Forecasting	MTNet
19-05-28	DF-Model		ICML 2019	Deep Factors for Forecasting	None
19-07-18	ESLSTM		IJoF 2020	A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting	None
19-07-25	MH-TAL		KDD 2019	Multi-Horizon Time Series Forecasting with Temporal Attention Learning	None
21-11-22	CRU		ICML 2022	Modeling Irregular Time Series with Continuous Recurrent Units	CRU
22-05-16	C2FAR		NIPS 2022	C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting	C2FAR
23-06-02	RNN-ODE-Adap		Arxiv 2023	Neural Differential Recurrent Neural Network with Adaptive Time Steps	RNN_ODE_Adap
23-08-22	SegRNN		Arxiv 2023	SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting	SegRNN
23-10-05	PA-RNN		NIPS 2023	Sparse Deep Learning for Time Series Data: Theory and Applications	None
23-11-03	WITRAN		NIPS 2023	WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting	WITRAN
23-12-14	DAN		AAAI 2024	Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series Forecasting	DAN
23-12-22	SutraNets		NIPS 2023	SutraNets: Sub-series Autoregressive Networks for Long-Sequence, Probabilistic Forecasting	None
24-01-17	RWKV-TS		Arxiv 2024	RWKV-TS: Beyond Traditional Recurrent Neural Network for Time Series Tasks	RWKV-TS
24-06-04	TGLRN		Arxiv 2024	Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting	None

MLP.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
19-05-24	NBeats🌟		ICLR 2020	N-BEATS: Neural Basis Expansion Analysis For Interpretable Time Series Forecasting	NBeats
21-04-12	NBeatsX		IJoF 2022	Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx	NBeatsX
22-01-30	N-HiTS🌟		AAAI 2023	N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting	N-HiTS
22-05-15	DEPTS		ICLR 2022	DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting	DEPTS
22-05-24	FreDo		Arxiv 2022	FreDo: Frequency Domain-based Long-Term Time Series Forecasting	None
22-05-26	DLinear🌟		AAAI 2023	Are Transformers Effective for Time Series Forecasting?	DLinear
22-06-24	TreeDRNet		Arxiv 2022	TreeDRNet: A Robust Deep Model for Long Term Time Series Forecasting	None
22-07-04	LightTS		Arxiv 2022	Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures	LightTS
22-08-10	STID		CIKM 2022	Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting	STID
23-01-30	SimST		Arxiv 2023	Do We Really Need Graph Neural Networks for Traffic Forecasting?	None
23-02-09	MTS-Mixers		Arxiv 2023	MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing	MTS-Mixers
23-03-10	TSMixer		Arxiv 2023	TSMixer: An all-MLP Architecture for Time Series Forecasting	None
23-04-17	TiDE🌟		Arxiv 2023	Long-term Forecasting with TiDE: Time-series Dense Encoder	TiDE
23-05-18	RTSF		Arxiv 2023	Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping	RTSF
23-05-30	Koopa🌟		NIPS 2023	Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors	Koopa
23-06-14	CI-TSMixer		KDD 2023	TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting	None
23-07-06	FITS🌟		ICLR 2024	FITS: Modeling Time Series with 10k Parameters	FITS
23-08-14	ST-MLP		Arxiv 2023	ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting	None
23-08-25	TFDNet		Arxiv 2023	TFDNet: Time-Frequency Enhanced Decomposed Network for Long-term Time Series Forecasting	None
23-11-10	FreTS		NIPS 2023	Frequency-domain MLPs are More Effective Learners in Time Series Forecasting	FreTS
23-12-11	MoLE		AISTATS 2024	Mixture-of-Linear-Experts for Long-term Time Series Forecasting	MoLE
23-12-22	STL		Arxiv 2023	Spatiotemporal-Linear: Towards Universal Multivariate Time Series Forecasting	None
24-01-04	U-Mixer		AAAI 2024	U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting	None
24-01-16	TimeMixer		ICLR 2024	TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting	TimeMixer
24-02-16	RPMixer		Arxiv 2024	Random Projection Layers for Multidimensional Time Sires Forecasting	None
24-02-20	IDEA		Arxiv 2024	When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting	None
24-03-04	CATS		ICML 2024	CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables	None
24-03-21	OLS		ICML 2024	An Analysis of Linear Time Series Forecasting Models	None
24-03-24	HDMixer		AAAI 2024	HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting	HDMixer
24-04-22	SOFTS		Arxiv 2024	SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion	SOFTS
24-05-02	SparseTSF		ICML 2024	SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters	SparseTSF
24-05-10	TEFN		Arxiv 2024	Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting	TEFN
24-05-22	PDMLP		Arxiv 2024	PDMLP: Patch-based Decomposed MLP for Long-Term Time Series Forecasting	None
24-06-06	AMD		Arxiv 2024	Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting	AMD
24-06-07	TimeSieve		Arxiv 2024	TimeSieve: Extracting Temporal Dynamics through Information Bottlenecks	TimeSieve

TCN/CNN.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
19-05-09	DeepGLO🌟		NIPS 2019	Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting	deepglo
19-05-22	DSANet		CIKM 2019	DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting	DSANet
19-12-11	MLCNN		AAAI 2020	Towards Better Forecasting by Fusing Near and Distant Future Visions	MLCNN
21-06-17	SCINet		NIPS 2022	SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction	SCINet
22-09-22	MICN		ICLR 2023	MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting	MICN
22-09-22	TimesNet🌟		ICLR 2023	TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis	TimesNet
23-02-23	LightCTS		SIGMOD 2023	LightCTS: A Lightweight Framework for Correlated Time Series Forecasting	LightCTS
23-05-25	TLNets		Arxiv 2023	TLNets: Transformation Learning Networks for long-range time-series prediction	TLNets
23-06-04	Cross-LKTCN		Arxiv 2023	Cross-LKTCN: Modern Convolution Utilizing Cross-Variable Dependency for Multivariate Time Series Forecasting Dependency for Multivariate Time Series Forecasting	None
23-06-12	MPPN		Arxiv 2023	MPPN: Multi-Resolution Periodic Pattern Network For Long-Term Time Series Forecasting	None
23-06-19	FDNet		KBS 2023	FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time Series Forecasting	FDNet
23-10-01	PatchMixer		Arxiv 2023	PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting	PatchMixer
23-11-01	WinNet		Arxiv 2023	WinNet:time series forecasting with a window-enhanced period extracting and interacting	None
23-11-27	ModernTCN🌟		ICLR 2024	ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis	ModernTCN
23-11-27	UniRepLKNet		Arxiv 2023	UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition	UniRepLKNet
24-03-03	ConvTimeNet		Arxiv 2024	ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis	ConvTimeNet
24-05-20	ATVCNet		Arxiv 2024	ATVCNet: Adaptive Extraction Network for Multivariate Long Sequence Time-Series Forecasting	None
24-05-24	FTMixer		Arxiv 2024	FTMixer: Frequency and Time Domain Representations Fusion for Time Series Modeling	FTMixer

GNN.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
17-09-14	STGCN🌟		IJCAI 2018	Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting	STGCN
19-05-31	Graph WaveNet		IJCAI 2019	Graph WaveNet for Deep Spatial-Temporal Graph Modeling	Graph-WaveNet
19-07-17	ASTGCN		AAAI 2019	Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting	ASTGCN
20-04-03	SLCNN		AAAI 2020	Spatio-Temporal Graph Structure Learning for Traffic Forecasting	None
20-04-03	GMAN		AAAI 2020	GMAN: A Graph Multi-Attention Network for Traffic Prediction	GMAN
20-05-03	MTGNN🌟		KDD 2020	Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks	MTGNN
21-03-13	StemGNN🌟		NIPS 2020	Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting	StemGNN
22-05-16	TPGNN		NIPS 2022	Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks	TPGNN
22-06-18	D2STGNN		VLDB 2022	Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting	D2STGNN
23-05-12	DDGCRN		PR 2023	A Decomposition Dynamic graph convolutional recurrent network for traffic forecasting	DDGCRN
23-05-30	HiGP		ICML 2024	Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting	None
23-07-10	NexuSQN		Arxiv 2023	Nexus sine qua non: Essentially connected neural networks for spatial-temporal forecasting of multivariate time series	None
23-11-10	FourierGNN		NIPS 2023	FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective	FourierGNN
23-12-05	SAMSGL		TETCI 2023	SAMSGL: Series-Aligned Multi-Scale Graph Learning for Spatio-Temporal Forecasting	None
23-12-27	TGCRN		ICDE 2024	Learning Time-aware Graph Structures for Spatially Correlated Time Series Forecasting	None
23-12-27	FCDNet		Arxiv 2023	FCDNet: Frequency-Guided Complementary Dependency Modeling for Multivariate Time-Series Forecasting	FCDNet
23-12-31	MSGNet		AAAI 2024	MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting	MSGNet
24-01-15	RGDAN		NN 2024	RGDAN: A random graph diffusion attention network for traffic prediction	RGDAN
24-01-16	BiTGraph		ICLR 2024	Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values	BiTGraph
24-01-24	TMP		AAAI 2024	Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence	None
24-02-16	HD-TTS		ICML 2024	Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling	None
24-05-17	HimNet		KDD 2024	Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting	HimNet
24-05-28	GFC-GNN		Arxiv 2024	ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks	None
24-06-18	SAGDFN		ICDE 2024	SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting	None

SSM (State Space Model).

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
18-05-18	DSSM	NIPS 2018	Deep State Space Models for Time Series Forecasting	None
19-08-10	DSSMF	IJCAI 2019	Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting	None
22-08-19	SSSD	TMLR 2022	Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models	SSSD
22-09-22	SpaceTime	ICLR 2023	Effectively Modeling Time Series with Simple Discrete State Spaces	SpaceTime
22-12-24	LS4	ICML 2023	Deep Latent State Space Models for Time-Series Generation	LS4
24-02-18	Attraos	Arxiv 2024	Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective	None
24-03-14	TimeMachine	Arxiv 2024	TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting	None
24-03-17	S-D-Mamba	Arxiv 2024	Is Mamba Effective for Time Series Forecasting?	S-D-Mamba
24-03-22	SiMBA	Arxiv 2024	SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series	Simba
24-03-29	TSM2	Arxiv 2024	MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selection	M2
24-04-23	Mambaformer	Arxiv 2024	Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting	Mambaformer
24-04-24	Bi-Mamba4TS	Arxiv 2024	Bi-Mamba4TS: Bidirectional Mamba for Time Series Forecasting	None
24-05-11	DTMamba	Arxiv 2024	DTMamba: Dual Twin Mamba for Time Series Forecasting	None
24-05-25	Time-SSM	Arxiv 2024	Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting	None
24-05-26	MambaTS	Arxiv 2024	MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting	None
24-06-06	Chimera	Arxiv 2024	Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models	None
24-06-08	C-Mamba	Arxiv 2024	C-Mamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting	None

Generation Model.

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
20-02-14	MAF🌟	ICLR 2021	Multivariate Probabilitic Time Series Forecasting via Conditioned Normalizing Flows	MAF
21-01-18	TimeGrad🌟	ICML 2021	Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting	TimeGrad
21-07-07	CSDI	NIPS 2021	CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation	CSDI
22-05-16	MANF	Arxiv 2022	Multi-scale Attention Flow for Probabilistic Time Series Forecasting	None
22-05-16	D3VAE	NIPS 2022	Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement	D3VAE
22-12-28	Hier-Transformer-CNF	Arxiv 2022	End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation	None
23-03-13	HyVAE	Arxiv 2023	Hybrid Variational Autoencoder for Time Series Forecasting	None
23-06-05	WIAE	Arxiv 2023	Non-parametric Probabilistic Time Series Forecasting via Innovations Representation	None
23-06-08	TimeDiff🌟	ICML 2023	Non-autoregressive Conditional Diffusion Models for Time Series Prediction	None
23-07-21	TSDiff	NIPS 2023	Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting	TSDiff
24-01-16	FTS-Diffusion	ICLR 2024	Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns	None
24-01-16	MG-TSD	ICLR 2024	MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process	MG-TSD
24-01-16	TMDM	ICLR 2024	Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting	None
24-01-16	mr-Diff	ICLR 2024	Multi-Resolution Diffusion Models for Time Series Forecasting	None
24-01-16	Diffusion-TS	ICLR 2024	Diffusion-TS: Interpretable Diffusion for General Time Series Generation	Diffusion-TS
24-01-16	SpecSTG	Arxiv 2024	SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting	SpecSTG
24-01-30	IN-Flow	Arxiv 2024	Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows	None
24-03-24	LDT	AAAI 2024	Latent Diffusion Transformer for Probabilistic Time Series Forecasting	None
24-06-04	GPD	Arxiv 2024	Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting	None
24-06-05	StochDiff	Arxiv 2024	Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting	None
24-06-11	ProFITi	Arxiv 2024	Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting	None

Time-index.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
17-05-25	ND		TNNLS 2017	Neural Decomposition of Time-Series Data for Effective Generalization	None
17-08-25	Prophet🌟		TAS 2018	Forecasting at Scale	Prophet
22-07-13	DeepTime		ICML 2023	Learning Deep Time-index Models for Time Series Forecasting	DeepTime
23-06-09	TimeFlow		Arxiv 2023	Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations	None
24-01-16	DAM🌟		ICLR 2024	DAM: A Foundation Model for Forecasting	None

Plug and Play (Model-Agnostic).

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
19-02-21	DAIN🌟	TNNLS 2020	Deep Adaptive Input Normalization for Time Series Forecasting	DAIN
19-09-19	DILATE	NIPS 2019	Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models	DILATE
21-07-19	TAN	NIPS 2021	Topological Attention for Time Series Forecasting	TAN
21-09-29	RevIN🌟	ICLR 2022	Reversible Instance Normalization for Accurate Time-Series Forecasting against Distribution Shift	RevIN
22-02-23	MQF2	AISTATS 2022	Multivariate Quantile Function Forecaster	None
22-05-18	FiLM	NIPS 2022	FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting	FiLM
23-02-18	FrAug	Arxiv 2023	FrAug: Frequency Domain Augmentation for Time Series Forecasting	FrAug
23-02-22	Dish-TS	AAAI 2023	Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting	Dish-TS
23-02-23	Adaptive Sampling	NIPSW 2022	Adaptive Sampling for Probabilistic Forecasting under Distribution Shift	None
23-04-19	RoR	ICML 2023	Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts	RoR
23-05-26	BetterBatch	Arxiv 2023	Better Batch for Deep Probabilistic Time Series Forecasting	None
23-05-28	PALS	Arxiv 2023	Adaptive Sparsity Level during Training for Efficient Time Series Forecasting with Transformers	None
23-06-09	FeatureProgramming	ICML 2023	Feature Programming for Multivariate Time Series Prediction	FeatureProgramming
23-07-18	Look_Ahead	SIGIR 2023	Look Ahead: Improving the Accuracy of Time-Series Forecasting by Previewing Future Time Features	Look_Ahead
23-09-14	QFCV	Arxiv 2023	Uncertainty Intervals for Prediction Errors in Time Series Forecasting	QFCV
23-10-09	PeTS	Arxiv 2023	Performative Time-Series Forecasting	PeTS
23-10-23	EDAIN	Arxiv 2023	Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks	EDAIN
23-11-19	TimeSQL	Arxiv 2023	TimeSQL: Improving Multivariate Time Series Forecasting with Multi-Scale Patching and Smooth Quadratic Loss	None
24-01-16	LIFT	ICLR 2024	Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators	None
24-01-16	RobustTSF	ICLR 2024	RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies	RobustTSF
24-02-04	FreDF	Arxiv 2024	FreDF: Learning to Forecast in Frequency Domain	FreDF
24-02-14	PDLS	ICML 2024	Transformers with Loss Shaping Constraints for Long-Term Time Series Forecasting	None
24-02-20	Leddam	ICML 2024	Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling	None
24-03-01	InfoTime	Arxiv 2024	Enhancing Multivariate Time Series Forecasting with Mutual Information-driven Cross-Variable and Temporal Modeling	None
24-03-13	wavelet-ML	Arxiv 2024	Leveraging Non-Decimated Wavelet Packet Features and Transformer Models for Time Series Forecasting	None
24-03-31	CCM	Arxiv 2024	From Similarity to Superiority: Channel Clustering for Time Series Forecasting	None
24-05-24	UnitNorm	Arxiv 2024	UnitNorm: Rethinking Normalization for Transformers in Time Series	UnitNorm
24-05-29	HCAN	Arxiv 2024	Hierarchical Classification Auxiliary Network for Time Series Forecasting	HCAN
24-06-07	TDT	Arxiv 2024	TDT Loss Takes It All: Integrating Temporal Dependencies among Targets into Non-Autoregressive Time Series Forecasting	None

LLM (Large Language Model).

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
22-09-20	PromptCast	TKDE 2023	PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting	PISA
23-02-23	FPT 🌟	NIPS 2023	One Fits All: Power General Time Series Analysis by Pretrained LM	One-Fits-All
23-05-17	LLMTime	NIPS 2023	Large Language Models Are Zero-Shot Time Series Forecasters	LLMTime
23-08-16	TEST	ICLR 2024	TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series	None
23-08-16	LLM4TS	Arxiv 2023	LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs	None
23-10-03	Time-LLM	ICLR 2024	Time-LLM: Time Series Forecasting by Reprogramming Large Language Models	None
23-10-08	TEMPO	ICLR 2024	TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting	TEMPO
23-10-12	Lag-Llama	Arxiv 2023	Lag-Llama: Towards Foundation Models for Time Series Forecasting	Lag-Llama
23-10-15	UniTime	WWW 2024	UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting	UniTime
23-11-03	ForecastPFN	NIPS 2023	ForecastPFN: Synthetically-Trained Zero-Shot Forecasting	ForecastPFN
23-11-24	FPT++ 🌟	Arxiv 2023	One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors	GPT4TS_Adapter
24-01-18	ST-LLM	Arxiv 2024	Spatial-Temporal Large Language Model for Traffic Prediction	None
24-02-01	LLMICL	Arxiv 2024	LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law	LLMICL
24-02-04	AutoTimes	Arxiv 2024	AutoTimes: Autoregressive Time Series Forecasters via Large Language Models	AutoTimes
24-02-05	Position Paper	Arxiv 2024	Position Paper: What Can Large Language Models Tell Us about Time Series Analysis	None
24-02-07	aLLM4TS	ICML 2024	Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning	None
24-02-16	TSFwithLLM	Arxiv 2024	Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities	None
24-02-25	LSTPrompt	Arxiv 2024	LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting	LSTPrompt
24-03-09	S2IP-LLM	ICML 2024	S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting	None
24-03-12	CALF	Arxiv 2024	CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning	CALF
24-03-12	Chronos 🌟	Arxiv 2024	Chronos: Learning the Language of Time Series	Chronos
24-04-17	TSandLanguage	Arxiv 2024	Language Models Still Struggle to Zero-shot Reason about Time Series	TSandLanguage
24-05-22	TGForecaster	Arxiv 2024	Beyond Trend and Periodicity: Guiding Time Series Forecasting with Textual Cues	tgtsf
24-05-23	Time-FFM	Arxiv 2024	Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting	None
24-06-03	TimeCMA	Arxiv 2024	TimeCMA: Towards LLM-Empowered Time Series Forecasting via Cross-Modality Alignment	None
24-06-07	LMGF	Arxiv 2024	A Language Model-Guided Framework for Mining Time Series with Distributional Shifts	None
24-06-12	Time-MMD	Arxiv 2024	Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis	Time-MMD

Pretrain & Representation.

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
20-10-06	TST	KDD 2021	A Transformer-based Framework for Multivariate Time Series Representation Learning	mvts_transformer
21-09-29	CoST	ICLR 2022	CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting	CoST
22-05-16	LaST	NIPS 2022	LaST: Learning Latent Seasonal-Trend Representations for Time Series Forecasting	LaST
22-06-18	STEP	KDD 2022	Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting	STEP
23-02-02	SimMTM	NIPS 2023	SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling	SimMTM
23-02-07	DBPM	ICLR 2024	Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach	None
23-03-01	TimeMAE	Arxiv 2023	TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders	TimeMAE
23-08-02	Floss	Arxiv 2023	Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach	floss
23-10-14	TimesFM	ICML 2024	A decoder-only foundation model for time-series forecasting	None
23-12-01	STD_MAE	Arxiv 2023	Spatio-Temporal-Decoupled Masked Pre-training for Traffic Forecasting	STD_MAE
23-12-25	TimesURL	AAAI 2024	TimesURL: Self-supervised Contrastive Learning for Universal Time Series Representation Learning	None
24-01-08	TTMs	Arxiv 2024	Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series	TTMs
24-01-16	SoftCLT	ICLR 2024	Soft Contrastive Learning for Time Series	None
24-01-16	PITS	ICLR 2024	Learning to Embed Time Series Patches Independently	PITS
24-01-16	T-Rep	ICLR 2024	T-Rep: Representation Learning for Time Series using Time-Embeddings	None
24-01-16	AutoTCL	ICLR 2024	Parametric Augmentation for Time Series Contrastive Learning	None
24-01-16	AutoCon	ICLR 2024	Self-Supervised Contrastive Forecasting	AutoCon
24-01-29	MLEM	Arxiv 2024	Self-Supervised Learning in Event Sequences: A Comparative Study and Hybrid Approach of Generative Modeling and Contrastive Learning	MLEM
24-02-04	Timer	ICML 2024	Timer: Generative Pre-trained Transformers Are Large Time Series Models	Timer
24-02-04	TimeSiam	ICML 2024	TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling	None
24-02-04	Moirai	ICML 2024	Unified Training of Universal Time Series Forecasting Transformers	Moirai
24-02-06	MOMENT	ICML 2024	MOMENT: A Family of Open Time-series Foundation Models	MOMENT
24-02-14	GTT	Arxiv 2024	Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction	GTT
24-02-26	TOTEM	Arxiv 2024	TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis	TOTEM
24-02-26	GPHT	Arxiv 2024	Generative Pretrained Hierarchical Transformer for Time Series Forecasting	None
24-02-29	UniTS	Arxiv 2024	UniTS: Building a Unified Time Series Model	UniTS
24-05-17	UniCL	Arxiv 2024	UniCL: A Universal Contrastive Learning Framework for Large Time Series Models	UniTS
24-05-24	NuwaTS	Arxiv 2024	NuwaTS: a Foundation Model Mending Every Incomplete Time Series	NuwaTS
24-05-24	ROSE	Arxiv 2024	ROSE: Register Assisted General Time Series Forecasting with Decomposed Frequency Learning	None
24-05-28	TSRM	Arxiv 2024	Time Series Representation Models	TSRM
24-05-30	S3	Arxiv 2024	Segment, Shuffle, and Stitch: A Simple Mechanism for Improving Time-Series Representations	S3

Domain Adaptation.

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
21-02-13	DAF	ICML 2022	Domain Adaptation for Time Series Forecasting via Attention Sharing	DAF
21-06-13	FOIL	ICML 2024	Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning

Online.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
22-02-23	FSNet		ICLR 2023	Learning Fast and Slow for Online Time Series Forecasting	FSNet
23-09-22	OneNet		NIPS 2023	OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling	OneNet
23-09-25	MemDA		CIKM 2023	MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation	None
24-01-08	ADCSD		Arxiv 2024	Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting	ADCSD
24-02-03	TSF-HD		Arxiv 2024	A Novel Hyperdimensional Computing Framework for Online Time Series Forecasting on the Edge	TSF-HD
24-02-20	SKI-CL		Arxiv 2024	Structural Knowledge Informed Continual Multivariate Time Series Forecasting	None
24-03-22	D3A		Arxiv 2024	Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt	None

Theory.

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
22-10-25	WaveBound	NIPS 2022	WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting	WaveBound
23-05-25	Ensembling	ICML 2023	Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting	None

Other.

Date	Method	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
16-12-05	TRMF	NIPS 2016	Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction	TRMF
23-05-23	DF2M	ICML 2024	Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization	None
24-01-16	STanHop-Net	ICLR 2024	STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction	None
24-02-02	SNN	ICML 2024	Efficient and Effective Time-Series Forecasting with Spiking Neural Networks	None
24-03-12	BayesNF	Arxiv 2024	Scalable Spatiotemporal Prediction with Bayesian Neural Fields	BayesNF
24-05-16	LaT-PFN	Arxiv 2024	LaT-PFN: A Joint Embedding Predictive Architecture for In-context Time-series Forecasting	None
24-05-24	ScalingLaw	Arxiv 2024	Scaling Law for Time Series Forecasting	ScalingLaw
24-06-04	CondTSF	Arxiv 2024	CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting	None
24-06-14	MTL	Arxiv 2024	Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting	None

Star History