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Awesome Time Series Forecasting/Prediction Papers

Awesome PRs Welcome Stars

This repository contains a reading list of 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. 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.

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

Some Additional Information.

🚩 I have marked some recommended papers with 🌟 (Just my personal preference 😉).

🚩 I have added a new category Irregular_time_series: models specifically designed for irregular time series.

🚩 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.

🚩 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.

Survey.

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 Arxiv 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 Arxiv 2023 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

Transformer.

Date Method Type Conference Paper Title and Paper Interpretation (In Chinese) Code
19-06-29 LogTrans univariate time series forecasting NIPS 2019 Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting flowforecast
19-12-19 TFT🌟 univariate time series forecasting IJoF 2021 Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting tft
20-01-23 InfluTrans univariate time series forecasting Arxiv 2020 Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case influenza transformer
20-06-05 AST univariate time series forecasting NIPS 2020 Adversarial Sparse Transformer for Time Series Forecasting AST
20-12-14 Informer🌟 multivariate time series forecasting AAAI 2021 Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Informer
21-05-22 ProTran multivariate time series forecasting NIPS 2021 Probabilistic Transformer for Time Series Analysis None
21-06-24 Autoformer🌟 multivariate time series forecasting NIPS 2021 Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting Autoformer
21-09-17 Aliformer univariate time series forecasting Arxiv 2021 From Known to Unknown: Knowledge-guided Transformer for Time-Series Sales Forecasting in Alibaba None
21-10-05 Pyraformer multivariate time series forecasting ICLR 2022 Pyraformer: Low-complexity Pyramidal Attention for Long-range Time Series Modeling and Forecasting Pyraformer
22-01-14 Preformer multivariate time series forecasting ICASSP 2023 Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series Forecasting Preformer
22-01-30 FEDformer🌟 multivariate time series forecasting ICML 2022 FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting FEDformer
22-02-03 ETSformer multivariate time series forecasting Arxiv 2022 ETSformer: Exponential Smoothing Transformers for Time-series Forecasting etsformer
22-02-07 TACTiS multivariate time series forecasting ICML 2022 TACTiS: Transformer-Attentional Copulas for Time Series TACTiS
22-04-28 Triformer multivariate time series forecasting IJCAI 2022 Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting Triformer
22-05-27 TDformer multivariate time series forecasting NIPSW 2022 First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting TDformer
22-05-28 Non-stationary Transformer multivariate time series forecasting NIPS 2022 Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting Non-stationary Transformers
22-06-08 Scaleformer multivariate time series forecasting ICLR 2023 Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting Scaleformer
22-08-14 Quatformer multivariate time series forecasting KDD 2022 Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting Quatformer
22-08-30 Persistence Initialization univariate time series forecasting Arxiv 2022 Persistence Initialization: A novel adaptation of the Transformer architecture for Time Series Forecasting None
22-09-08 W-Transformers univariate time series forecasting Arxiv 2022 W-Transformers: A Wavelet-based Transformer Framework for Univariate Time Series Forecasting w-transformer
22-09-22 Crossformer multivariate time series forecasting ICLR 2023 Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting Crossformer
22-09-22 PatchTST🌟 univariate time series forecasting ICLR 2023 A Time Series is Worth 64 Words: Long-term Forecasting with Transformers PatchTST
22-11-29 AirFormer spatio-temporal forecasting AAAI 2023 AirFormer: Predicting Nationwide Air Quality in China with Transformers AirFormer
23-01-19 PDFormer spatio-temporal forecasting AAAI 2023 PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction PDFormer
23-03-01 ViTST Irregular_time_series NIPS 2023 Time Series as Images: Vision Transformer for Irregularly Sampled Time Series ViTST
23-05-20 CARD multivariate time series forecasting Arxiv 2023 Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer None
23-05-24 JTFT multivariate time series forecasting Arxiv 2023 A Joint Time-frequency Domain Transformer for Multivariate Time Series Forecasting None
23-05-30 HSTTN spatio-temporal forecasting IJCAI 2023 Long-term Wind Power Forecasting with Hierarchical Spatial-Temporal Transformer None
23-05-30 Client multivariate time series forecasting Arxiv 2023 Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting Client
23-05-30 Taylorformer univariate time series forecasting Arxiv 2023 Taylorformer: Probabilistic Predictions for Time Series and other Processes Taylorformer
23-06-05 Corrformer🌟 spatio-temporal forecasting NMI 2023 Interpretable weather forecasting for worldwide stations with a unified deep model Corrformer
23-06-14 GCformer multivariate time series forecasting CIKM 2023 GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting GCformer
23-07-04 SageFormer multivariate time series forecasting Arxiv 2023 SageFormer: Series-Aware Graph-Enhanced Transformers for Multivariate Time Series Forecasting None
23-07-10 DifFormer multivariate time series forecasting TPAMI 2023 DifFormer: Multi-Resolutional Differencing Transformer With Dynamic Ranging for Time Series Analysis None
23-07-27 HUTFormer spatio-temporal forecasting Arxiv 2023 HUTFormer: Hierarchical U-Net Transformer for Long-Term Traffic Forecasting None
23-08-07 DSformer multivariate time series forecasting CIKM 2023 DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction None
23-08-09 SBT multivariate time series forecasting KDD 2023 Sparse Binary Transformers for Multivariate Time Series Modeling None
23-08-09 PETformer multivariate time series forecasting Arxiv 2023 PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer None
23-10-02 TACTiS-2 multivariate time series forecasting Arxiv 2023 TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series None
23-10-03 PrACTiS multivariate time series forecasting Arxiv 2023 PrACTiS: Perceiver-Attentional Copulas for Time Series None
23-10-10 iTransformer multivariate time series forecasting Arxiv 2023 iTransformer: Inverted Transformers Are Effective for Time Series Forecasting iTransformer
23-10-26 ContiFormer Irregular_time_series NIPS 2023 ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling None
23-10-31 BasisFormer multivariate time series forecasting NIPS 2023 BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis basisformer

RNN.

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

MLP.

Date Method Type Conference Paper Title and Paper Interpretation (In Chinese) Code
19-05-24 NBeats🌟 univariate time series forecasting ICLR 2020 N-BEATS: Neural Basis Expansion Analysis For Interpretable Time Series Forecasting NBeats
21-04-12 NBeatsX univariate time series forecasting IJoF 2022 Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx NBeatsX
22-01-30 N-HiTS🌟 univariate time series forecasting AAAI 2023 N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting N-HiTS
22-05-15 DEPTS univariate time series forecasting ICLR 2022 DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting DEPTS
22-05-24 FreDo univariate time series forecasting Arxiv 2022 FreDo: Frequency Domain-based Long-Term Time Series Forecasting None
22-05-26 DLinear🌟 univariate time series forecasting AAAI 2023 Are Transformers Effective for Time Series Forecasting? DLinear
22-06-24 TreeDRNet multivariate time series forecasting Arxiv 2022 TreeDRNet: A Robust Deep Model for Long Term Time Series Forecasting None
22-07-04 LightTS multivariate time series forecasting Arxiv 2022 Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures LightTS
22-08-10 STID multivariate time series forecasting CIKM 2022 Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting STID
23-01-30 SimST spatio-temporal forecasting Arxiv 2023 Do We Really Need Graph Neural Networks for Traffic Forecasting? None
23-02-09 MTS-Mixers multivariate time series forecasting Arxiv 2023 MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing MTS-Mixers
23-03-10 TSMixer multivariate time series forecasting Arxiv 2023 TSMixer: An all-MLP Architecture for Time Series Forecasting None
23-04-17 TiDE🌟 multivariate time series forecasting Arxiv 2023 Long-term Forecasting with TiDE: Time-series Dense Encoder TiDE
23-05-18 RTSF univariate time series forecasting Arxiv 2023 Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping RTSF
23-05-30 Koopa🌟 multivariate time series forecasting NIPS 2023 Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors Koopa
23-06-14 CI-TSMixer multivariate time series forecasting KDD 2023 TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting None
23-07-06 FITS univariate time series forecasting Arxiv 2023 FITS: Modeling Time Series with 10k Parameters FITS
23-08-14 ST-MLP spatio-temporal forecasting Arxiv 2023 ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting None
23-08-25 TFDNet multivariate time series forecasting Arxiv 2023 TFDNet: Time-Frequency Enhanced Decomposed Network for Long-term Time Series Forecasting None

TCN/CNN.

Date Method Type Conference Paper Title and Paper Interpretation (In Chinese) Code
19-05-09 DeepGLO🌟 multivariate time series forecasting NIPS 2019 Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting deepglo
19-05-22 DSANet multivariate time series forecasting CIKM 2019 DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting DSANet
19-12-11 MLCNN multivariate time series forecasting AAAI 2020 Towards Better Forecasting by Fusing Near and Distant Future Visions MLCNN
21-06-17 SCINet multivariate time series forecasting NIPS 2022 SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction SCINet
22-09-22 MICN multivariate time series forecasting ICLR 2023 MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting MICN
22-09-22 TimesNet🌟 multivariate time series forecasting ICLR 2023 TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis TimesNet
23-02-23 LightCTS multivariate time series forecasting SIGMOD 2023 LightCTS: A Lightweight Framework for Correlated Time Series Forecasting LightCTS
23-05-25 TLNets multivariate time series forecasting Arxiv 2023 TLNets: Transformation Learning Networks for long-range time-series prediction TLNets
23-06-04 Cross-LKTCN multivariate time series forecasting 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 multivariate time series forecasting Arxiv 2023 MPPN: Multi-Resolution Periodic Pattern Network For Long-Term Time Series Forecasting None
23-06-19 FDNet multivariate time series forecasting KBS 2023 FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time Series Forecasting FDNet
23-10-01 PatchMixer univariate time series forecasting Arxiv 2023 PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting PatchMixer
23-11-01 WinNet univariate time series forecasting Arxiv 2023 WinNet:time series forecasting with a window-enhanced period extracting and interacting None

GNN.

Date Method Type Conference Paper Title and Paper Interpretation (In Chinese) Code
17-09-14 STGCN🌟 spatio-temporal forecasting IJCAI 2018 Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting STGCN
19-05-31 Graph WaveNet spatio-temporal forecasting IJCAI 2019 Graph WaveNet for Deep Spatial-Temporal Graph Modeling Graph-WaveNet
19-07-17 ASTGCN spatio-temporal forecasting AAAI 2019 Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting ASTGCN
20-04-03 SLCNN spatio-temporal forecasting AAAI 2020 Spatio-Temporal Graph Structure Learning for Traffic Forecasting None
20-04-03 GMAN spatio-temporal forecasting AAAI 2020 GMAN: A Graph Multi-Attention Network for Traffic Prediction GMAN
20-05-03 MTGNN🌟 multivariate time series forecasting KDD 2020 Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks MTGNN
21-03-13 StemGNN🌟 multivariate time series forecasting NIPS 2020 Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting StemGNN
22-05-16 TPGNN multivariate time series forecasting NIPS 2022 Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks TPGNN
22-06-18 D2STGNN spatio-temporal forecasting VLDB 2022 Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting D2STGNN
23-07-10 NexuSQN spatio-temporal forecasting Arxiv 2023 Nexus sine qua non: Essentially connected neural networks for spatial-temporal forecasting of multivariate time series 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

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 None

Time-index.

Date Method Type Conference Paper Title and Paper Interpretation (In Chinese) Code
17-05-25 ND univariate time series forecasting TNNLS 2017 Neural Decomposition of Time-Series Data for Effective Generalization None
17-08-25 Prophet🌟 univariate time series forecasting TAS 2018 Forecasting at Scale Prophet
22-07-13 DeepTime multivariate time series forecasting ICML 2023 Learning Deep Time-index Models for Time Series Forecasting DeepTime
23-06-09 TimeFlow univariate time series forecasting Arxiv 2023 Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations 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

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
23-02-23 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
23-08-02 Floss Arxiv 2023 Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach floss
23-08-16 TEST Arxiv 2023 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 Arxiv 2023 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models None
23-10-08 TEMPO Arxiv 2023 TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting None
23-10-12 Lag-Llama Arxiv 2023 Lag-Llama: Towards Foundation Models for Time Series Forecasting Lag-Llama
23-10-15 UniTime Arxiv 2023 UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting None
23-11-03 ForecastPFN NIPS 2023 ForecastPFN: Synthetically-Trained Zero-Shot Forecasting ForecastPFN

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

Online.

Date Method Type Conference Paper Title and Paper Interpretation (In Chinese) Code
22-02-23 FSNet multivariate time series forecasting ICLR 2023 Learning Fast and Slow for Online Time Series Forecasting FSNet
23-09-22 OneNet multivariate time series forecasting NIPS 2023 OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling OneNet
23-09-25 MemDA spatio-temporal forecasting CIKM 2023 MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation 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