NeurIPS 2024 | 时间序列（Time Series）论文总结

NeurIPS 2024于2024年12月10号-12月15号在加拿大温哥华举行（Vancouver, Canada）,录取率25.8%

本文总结了NeurIPS 2024有关时间序列（time series data）的相关论文，主要包含如有疏漏，欢迎大家补充。

时间序列Topic：预测，插补，分类，生成，因果分析，异常检测，LLM以及基础模型等内容。总计61篇，其中正会55篇，D&B Track6篇

预测：1-29 异常检测：30，57 分类：32，54，55 表示学习：37，39，40 生成：31，41，42，60 时序分析：33，34，36 大语言模型：7，10，24，52 基础模型：16，29，35，53 扩散模型：1，31，42，43

1 Retrieval-Augumented Diffusion Models for Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/94339

作者：Jingwei Liu, Ling Yang, Hongyan Li, Shenda Hong

关键词：预测，扩散模型，检索增强

2 Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective

链接：https://neurips.cc/virtual/2024/poster/94220

arXiv：https://arxiv.org/abs/2402.11463

作者：Jiaxi Hu, Yuehong Hu, Wei Chen, Ming Jin, Shirui Pan, Qingsong Wen, Yuxuan Liang

关键词：长时预测

Attraos

3 Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95175

作者：Zongjiang Shang, Ling Chen, Binqing Wu, Dongliang Cui

关键词：预测，多尺度，超图，Transformer

4 FilterNet: Harnessing Frequency Filters for Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/93257

作者：Kun Yi, Wei Fan, Qi Zhang, Hui He, Jingru Fei, Shufeng Hao, Defu Lian

关键词：预测，频率过滤

5 Frequency Adaptive Normalization For Non-stationary Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95063

arXiv：https://arxiv.org/abs/2409.20371

作者：Weiwei Ye · Songgaojun Deng · Qiaosha Zou · Ning Gui

关键词：预测，非平稳

FAN

6 Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective

链接：https://neurips.cc/virtual/2024/poster/96026

arXiv：https://arxiv.org/abs/2409.18696

作者：Chengsen Wang · Qi Qi · Jingyu Wang · Haifeng Sun · Zirui Zhuang · Jinming Wu · Jianxin Liao

关键词：预测，稳健性

GLAFF

7 AutoTimes: Autoregressive Time Series Forecasters via Large Language Models

链接：https://neurips.cc/virtual/2024/poster/95975

arXiv：https://arxiv.org/abs/2402.02370

作者：Yong Liu · Guo Qin · Xiangdong Huang · Jianmin Wang · Mingsheng Long

关键词：预测，LLM，自回归

AI论文速读 | AutoTimes：利用大语言模型的自回归时间序列预测器

AutoTimes

8 DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95167

作者：Tao Dai · Beiliang Wu · Peiyuan Liu · Naiqi Li · Xue Yuerong · Shu-Tao Xia · Zexuan Zhu

关键词：预测，非平稳，双域

9 BackTime: Backdoor Attacks on Multivariate Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95645

arXiv：https://arxiv.org/abs/2410.02195

作者：Xiao Lin · Zhining Liu · Dongqi Fu · Ruizhong Qiu · Hanghang Tong

关键词：预测，后门攻击

10 [Spotlight] Are Language Models Actually Useful for Time Series Forecasting?

链接：https://neurips.cc/virtual/2024/poster/96085

arXiv：https://arxiv.org/abs/2410.02195

作者：Mingtian Tan · Mike Merrill · Vinayak Gupta · Tim Althoff · Tom Hartvigsen

关键词：预测，LLM

备注：大胆之作，去掉LLM效果更好了。

机器之心：LLM用于时序预测真的不行，连推理能力都没用到

圆圆的算法笔记：预训练大语言模型对时间序列预测真的有用吗？去掉预训练LLM效果反而提升

11 Rethinking Fourier Transform for Long-term Time Series Forecasting: A Basis Functions Perspective

链接：https://neurips.cc/virtual/2024/poster/96209

作者：Runze Yang · Longbing Cao · JIE YANG · li jianxun

关键词：长时预测，傅里叶变换

12 Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/94305

作者：Bong Gyun Kang · Dongjun Lee · HyunGi Kim · Dohyun Chung · Sungroh Yoon

关键词：预测，谱域注意力，长期依赖

13 Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/93133

arXiv：https://arxiv.org/abs/2401.11929

作者：Jinliang Deng · Feiyang Ye · Du Yin · Xuan Song · Ivor Tsang · Hui Xiong

关键词：长时预测

SSCNN

14 Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics

链接：https://neurips.cc/virtual/2024/poster/94383

作者：Xiaodan Chen · Xiucheng Li · Xinyang Chen · Zhijun Li

关键词：预测，可解释性，动态性

15 DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching

链接：https://neurips.cc/virtual/2024/poster/96221

作者：Donghao Luo · Xue Wang

关键词：预测，Transformer，Patch

16 Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95835

arXiv：https://arxiv.org/abs/2405.14252

作者：Qingxiang Liu · Xu Liu · Chenghao Liu · Qingsong Wen · Yuxuan Liang

关键词：预测，联邦学习，基础模型

Time-FFM

17 PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/92992

arXiv：https://arxiv.org/abs/2409.17703

代码：https://github.com/Water2sea/TPGN

作者：Yuxin Jia · Youfang Lin · Jing Yu · Shuo Wang · Tianhao Liu · Huaiyu Wan

关键词：长时预测，RNN

PGN

18 SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion

链接：https://neurips.cc/virtual/2024/poster/96390

arXiv：https://arxiv.org/abs/2404.14197

代码：https://github.com/Secilia-Cxy/SOFTS

作者：Han Lu · Xu-Yang Chen · Han-Jia Ye · De-Chuan Zhan

关键词：预测，MLP

SOFTS

19 Multivariate Probabilistic Time Series Forecasting with Correlated Errors

链接：https://neurips.cc/virtual/2024/poster/94440

arXiv：https://arxiv.org/abs/2409.18479

作者：Zhihao Zheng · Lijun Sun

关键词：概率预测，不确定性量化

20 CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns

链接：https://neurips.cc/virtual/2024/poster/94391

arXiv：https://arxiv.org/abs/2409.18479

代码：https://github.com/ACAT-SCUT/CycleNet

作者：Shengsheng Lin · Weiwei Lin · Xinyi Hu · Wentai Wu · Ruichao Mo · Haocheng Zhong

关键词：长时预测，周期建模

科学最Top：时序论文28｜CycleNet：通过对周期模式进行建模增强时间序列预测

CycleNet

21 Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95988

作者：Romain Ilbert · Malik Tiomoko · Cosme Louart · Ambroise Odonnat · Vasilii Feofanov · Themis Palpanas · Ievgen Redko

关键词：预测，多任务回归，随机矩阵理论

22 CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95627

arXiv：https://arxiv.org/abs/2406.02131

代码：https://github.com/RafaDD/CondTSF

作者：Jianrong Ding · Zhanyu Liu · Guanjie Zheng · Haiming Jin · Linghe Kong

关键词：预测，插件

CondTSF

23 Scaling Law for Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/96119

arXiv：https://arxiv.org/pdf/2405.15124

代码：https://github.com/JingzheShi/ScalingLawForTimeSeriesForecasting

作者：Jingzhe Shi · Qinwei Ma · Huan Ma · Lei Li

关键词：预测，Scaling Law

24 From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection

链接：https://neurips.cc/virtual/2024/poster/93316

arXiv：https://arxiv.org/abs/2409.17515

作者：Xinlei Wang · Maike Feng · Jing Qiu · Jinjin Gu · Junhua Zhao

关键词：预测，LLM，事件融合

25 From Similarity to Superiority: Channel Clustering for Time Series Forecasting

链接：https://neurips.cc/virtual/2024/poster/95539

arXiv：https://arxiv.org/abs/2404.01340

作者：Jialin Chen · Jan Eric Lenssen · Aosong Feng · Weihua Hu · Matthias Fey · Leandros Tassiulas · Jure Leskovec · Rex Ying

关键词：预测，通道聚类

AI论文速读 | CCM：从相似到超越：时间序列预测的通道聚类

CCM

26 TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

链接：https://neurips.cc/virtual/2024/poster/95770

arXiv：https://arxiv.org/abs/2402.19072

作者：Yuxuan Wang · Haixu Wu · Jiaxiang Dong · Guo Qin · Haoran Zhang · Yong Liu · Yun-Zhong Qiu · Jianmin Wang · Mingsheng Long

关键词：预测，外生变量，Transformer

AI论文速读 | TimeXer：让 Transformer能够利用外部变量进行时间序列预测

TimeXer

27 ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer

链接：https://neurips.cc/virtual/2024/poster/93264

作者：Jiawen Zhang · Shun Zheng · Xumeng Wen · Xiaofang Zhou · Jiang Bian · Jia Li

关键词：预测，稳健性，Patch

28 Are Self-Attentions Effective for Time Series Forecasting?

链接：https://neurips.cc/virtual/2024/poster/94012

arXiv：https://arxiv.org/abs/2405.16877

作者：Dongbin Kim · Jinseong Park · Jaewook Lee · Hoki Kim

关键词：预测，交叉注意力

29 Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

链接：https://neurips.cc/virtual/2024/poster/96748

arXiv：https://arxiv.org/abs/2401.03955

代码：https://github.com/ibm-granite/granite-tsfm/tree/main/tsfm_public/models/tinytimemixer

Huggingface：https://huggingface.co/ibm-granite/granite-timeseries-ttm-v1

作者：Vijay Ekambaram · Arindam Jati · Pankaj Dayama · Sumanta Mukherjee · Nam Nguyen · WESLEY M GIFFORD · Chandra Reddy · Jayant Kalagnanam

关键词：零样本/少样本预测

AI蜗牛车：IBM Research：轻量级时间序列大模型提升Few-shot Learning时序预测效果

TTMs

30 SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series

链接：https://neurips.cc/virtual/2024/poster/94119

作者：Zhihao Dai · Ligang He · Shuanghua Yang · Matthew Leeke

关键词：异常检测，空间关联感知

31 Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series

链接：https://neurips.cc/virtual/2024/poster/96819

作者：Ilan Naiman · Nimrod Berman · Itai Pemper · Idan Arbiv · Gal Fadlon · Omer Asher · Omri Azencot

关键词：分类（长时），判别（短时）

32 Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification

链接：https://neurips.cc/virtual/2024/poster/93973

arXiv：https://arxiv.org/abs/2408.00041

作者：Junru Chen · Tianyu Cao · Jing Xu · Jiahe Li · Zhilong Chen · Tao Xiao · YANG YANG

关键词：分类

时序人：NeurIPS 2024 | 分段时序多分类任务下的一致性学习框架

Con4m

33 Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis

链接：https://neurips.cc/virtual/2024/poster/96575

作者：Qiang Wu · Gechang Yao · Zhixi Feng · Yang Shuyuan

关键词：分析，Transformer

34 Shape analysis for time series

链接：https://neurips.cc/virtual/2024/poster/95718

作者：Thibaut Germain · Samuel Gruffaz · Charles Truong · Alain Durmus · Laurent Oudre

关键词：分析，生理时序，无监督

35 UNITS: A Unified Multi-Task Time Series Model

链接：https://neurips.cc/virtual/2024/poster/93709

arXiv：https://arxiv.org/abs/2403.00131

代码：https://github.com/mims-harvard/UniTS

作者：Shanghua Gao · Teddy Koker · Owen Queen · Tom Hartvigsen · Theodoros Tsiligkaridis · Marinka Zitnik

关键词：多任务，基础模型

AI论文速读 | UniTS：构建统一的时间序列模型

36 Large Pre-trained time series models for cross-domain Time series analysis tasks

链接：https://neurips.cc/virtual/2024/poster/93205

arXiv：https://arxiv.org/abs/2311.11413

代码：https://github.com/kage08/SegmentTS/

作者：Harshavardhan Prabhakar Kamarthi · B. Aditya Prakash

关键词：分析，跨域，预训练

LPTM

37 Segment, Shuffle, and Stitch: A Simple Mechanism for Improving Time-Series Representations

链接：https://neurips.cc/virtual/2024/poster/92935

arXiv：https://arxiv.org/abs/2405.20082

代码：https://github.com/shivam-grover/S3-TimeSeries

作者：Shivam Grover · Amin Jalali · Ali Etemad

关键词：表示学习

S3

38 Task-oriented Time Series Imputation Evaluation via Generalized Representers

链接：https://neurips.cc/virtual/2024/poster/93717

代码：https://github.com/hkuedl/Task-Oriented-Imputation

作者：Zhixian Wang · Linxiao Yang · Liang Sun · Qingsong Wen · Yi Wang

关键词：插补，评估方法

39 Exploiting Representation Curvature for Boundary Detection in Time Series

链接：https://neurips.cc/virtual/2024/poster/94837

作者：Yooju Shin · Jaehyun Park · Susik Yoon · Hwanjun Song · Byung Suk Lee · Jae-Gil Lee

关键词：边界检测

40 Learning diverse causally emergent representations from time series data

链接：https://neurips.cc/virtual/2024/poster/92973

作者：David McSharry · Christos Kaplanis · Fernando Rosas · Pedro A.M Mediano

关键词：因果涌现

41 SDformer: Similarity-driven Discrete Transformer For Time Series Generation

链接：https://neurips.cc/virtual/2024/poster/94642

作者：Zhicheng Chen · FENG SHIBO · Zhong Zhang · Xi Xiao · Xingyu Gao · Peilin Zhao

关键词：时间序列生成，离散Transformer

42 FIDE: Frequency-Inflated Conditional Diffusion Model for Extreme-Aware Time Series Generation

链接：https://neurips.cc/virtual/2024/poster/96595

作者：Asadullah Hill Galib · Pang-Ning Tan · Lifeng Luo

关键词：时间序列生成，条件扩散模型

43 ANT: Adaptive Noise Schedule for Time Series Diffusion Models

链接：https://neurips.cc/virtual/2024/poster/96850

作者：Seunghan Lee · Kibok Lee · Taeyoung Park

关键词：扩散模型，自适应噪声

44 Trajectory Flow Matching with Applications to Clinical Time Series Modelling

链接：https://neurips.cc/virtual/2024/poster/94212

作者：Xi (Nicole) Zhang · Yuan Pu · Yuki Kawamura · Andrew Loza · Yoshua Bengio · Dennis Shung · Alexander Tong

关键词：建模，临床时间序列，流匹配

45 Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models

链接：https://neurips.cc/virtual/2024/poster/93680

arXiv：https://arxiv.org/abs/2406.04320

作者：Ali Behrouz · Michele Santacatterina · Ramin Zabih

关键词：建模，状态空间模型

Chimera

46 Reinforced Cross-Domain Knowledge Distillation on Time Series Data

链接：https://neurips.cc/virtual/2024/poster/93330

作者：QING XU · Min Wu · Xiaoli Li · Kezhi Mao · Zhenghua Chen

关键词：知识蒸馏，无监督域适应

47 Boosting Transferability and Discriminability for Time Series Domain Adaptation

链接：https://neurips.cc/virtual/2024/poster/94429

作者：Mingyang Liu · Xinyang Chen · Yang Shu · Xiucheng Li · Weili Guan · Liqiang Nie

关键词：域适应，迁移性，判别性

48 Towards Editing Time Series

链接：https://neurips.cc/virtual/2024/poster/93468

作者：Baoyu Jing · Shuqi Gu · Tianyu Chen · Zhiyu Yang · Dongsheng Li · Jingrui He · Kan Ren

关键词：时间序列编辑，合成时间序列

49 Conformalized Time Series with Semantic Features

链接：https://neurips.cc/virtual/2024/poster/95653

作者：Baiting Chen · Zhimei Ren · Lu Cheng

关键词：共形预测，分布偏移

50 ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions

链接：https://neurips.cc/virtual/2024/poster/93042

作者：Etienne Vareille · Michele Linardi · Vassilis Christophides · Ioannis Tsamardinos

关键词：时间序列选择

51 Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series

链接：https://neurips.cc/virtual/2024/poster/93348

作者：Giangiacomo Mercatali · Andre Freitas · Jie Chen

关键词：不规则时间序列，因果，常微分方程

52 Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization

链接：https://neurips.cc/virtual/2024/poster/94588

作者：Chengtao Jian · Kai Yang · Yang Jiao

关键词：分布外泛化，LLM

53 UniMTS: Unified Pre-training for Motion Time Series

链接：https://neurips.cc/virtual/2024/poster/96073

作者：Xiyuan Zhang · Diyan Teng · Ranak Roy Chowdhury · Shuheng Li · Dezhi Hong · Rajesh Gupta · Jingbo Shang

关键词：运动时间序列，预训练

54 Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification

链接：https://neurips.cc/virtual/2024/poster/93940

arXiv：https://arxiv.org/abs/2405.19363

代码：https://github.com/DL4mHealth/Medformer

作者：Yihe Wang · Nan Huang · Taida Li · Yujun Yan · Xiang Zhang

关键词：分类，医疗时间序列

Medformer

55 Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification

链接：https://neurips.cc/virtual/2024/poster/93522

作者：Yunshi Wen · Tengfei Ma · Lily Weng · Lam Nguyen · Anak Agung Julius

关键词：分类，可解释性，泛化性

D&B Track

56 IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark

链接：https://neurips.cc/virtual/2024/poster/97776

arXiv：https://arxiv.org/abs/2405.16069

代码：https://github.com/Healthy-AI/IncomeSCM

作者：Fredrik Johansson（独立作者）

关键词：因果估计，模拟器

IncomeSCM

57 The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark

链接：https://neurips.cc/virtual/2024/poster/97690

代码：https://github.com/TheDatumOrg/TSB-AD

作者：Qinghua Liu · John Paparrizos

关键词：异常检测，benchmark

TSB-AD

58 Building Timeseries Dataset: Empowering Large-Scale Building Analytics

链接：https://neurips.cc/virtual/2024/poster/97839

arXiv：https://arxiv.org/abs/2406.08990

代码：https://github.com/cruiseresearchgroup/DIEF_BTS

作者：Arian Prabowo · Xiachong LIN · Imran Razzak · Hao Xue · Emily Yap · Matthew Amos · Flora Salim

关键词：建筑时间序列，数据集，metadata

59 Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis

链接：https://neurips.cc/virtual/2024/poster/97582

arXiv：https://arxiv.org/abs/2406.08627

library代码：https://github.com/AdityaLab/MM-TSFlib

dataset 代码：https://github.com/AdityaLab/Time-MMD

作者：Haoxin Liu · Shangqing Xu · Zhiyuan Zhao · Lingkai Kong · Harshavardhan Prabhakar Kamarthi · Aditya Sasanur · Megha Sharma · Jiaming Cui · Qingsong Wen · Chao Zhang · B. Aditya Prakash

关键词：数据集，分析，多模态，多域

Time-MMD

60 TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series

链接：https://neurips.cc/virtual/2024/poster/97532

arXiv：https://arxiv.org/abs/2305.11567

作者：Alexander Nikitin · Letizia Iannucci · Samuel Kaski

关键词：时间序列生成，合成时间序列，框架

60 TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series

链接：https://neurips.cc/virtual/2024/poster/97532

arXiv：https://arxiv.org/abs/2305.11567

作者：Alexander Nikitin · Letizia Iannucci · Samuel Kaski

关键词：时间序列生成，合成时间序列，框架

Time-MMD

61 ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons

链接：https://neurips.cc/virtual/2024/poster/97527

arXiv：https://arxiv.org/abs/2310.07446

代码：https://github.com/microsoft/ProbTS

作者：Jiawen Zhang · Xumeng Wen · Zhenwei Zhang · Shun Zheng · Jia Li · Jiang Bian

关键词：概率预测，benchmark

微软亚洲研究院：ProbTS：时间序列预测的统一评测框架

ProbTS

相关链接

NeurIPS 24 Accepted Papers：https://neurips.cc/virtual/2024/papers.html

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