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ICML 2023 | 时间序列(Time Series)和时空数据(Spatial-Temporal)论文总结

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时空探索之旅
发布2024-11-19 16:18:34
发布2024-11-19 16:18:34
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文章被收录于专栏:时空探索之旅时空探索之旅

2023ICML(International Conference on Machine Learning,国际机器学习会议)在2023年7月23日-29日在美国夏威夷举行。2023年ICML 共收到 6538 份投稿,其中 1827 份被接收,接收率约为 27.9%。(好像ICML24要开始第一轮rebuttal了,蹭蹭热度)

本文总结了ICML 23有关时间序列(Time Series)时空(Spatial-temporal) 的相关论文,如有疏漏,欢迎大家补充。(官网是有poster的,就直接用poster作为论文配图)

时间序列Topic:插补,预测,因果,表示学习,无监督,对比学习,不确定性等

时空数据Topic:AI4Science,GeoAI,时空预测等

时间序列(time series)

时序标题词云

1. Probabilistic Imputation for Time-series Classification with Missing Data

大会论文链接https://icml.cc/virtual/2023/poster/23522

PMLR链接https://proceedings.mlr.press/v202/kim23m

作者:SeungHyun Kim · Hyunsu Kim · EungGu Yun · Hwangrae Lee · Jaehun Lee · Juho Lee

机构:韩国科学技术院(KAIST),赛视智能(Saige Research),三星研究院

关键词:时间序列数据插补,概率模型,不确定性

2. Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation

大会论文链接https://icml.cc/virtual/2023/poster/24369

PMLR链接https://proceedings.mlr.press/v202/chen23f.html

代码https://github.com/morganstanley/MSML/tree/main/papers/Conditional_Schrodinger_Bridge_Imputation

作者:Yu Chen · Wei Deng · Shikai Fang · Fengpei Li · Tianjiao N Yang · Yikai Zhang · Kashif Rasul · Shandian Zhe · Anderson Schneider · Yuriy N evmyvaka

机构:摩根士丹利,犹他大学(Utah),埃默里大学(Emory)

关键词:时间序列插补、概率模型

3. Deep Latent State Space Models for Time-Series Generation

大会论文链接https://icml.cc/virtual/2023/poster/24503

PMLR链接https://proceedings.mlr.press/v202/zhou23i.html

作者:Linqi Zhou · Michael Poli · Winnie Xu · Stefano Massaroli · Stefano Ermon

机构:斯坦福大学(Stanford),多伦多大学(Toronto),MILA

关键词:时间序列生成

4. Neural Stochastic Differential Games for Time-series Analysis

大会论文链接https://icml.cc/virtual/2023/poster/25204

PMLR链接https://proceedings.mlr.press/v202/park23j.html

代码https://github.com/LGAI-AML/MaSDEs

作者:Sungwoo Park, Byoungwoo Park, Moontae Lee, Changhee Lee

机构:LG AI Research,韩国中央大学,伊利诺伊大学芝加哥分校(UIC)

关键词:时间序列分析

5. Context Consistency Regularization for Label Sparsity in Time Series

大会论文链接https://icml.cc/virtual/2023/poster/24019

PMLR链接https://proceedings.mlr.press/v202/shin23e.html

代码https://github.com/kaist-dmlab/CrossMatch

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

机构:KAIST,伊利诺伊大学香槟分校(UIUC),亚马逊AI Lab(AWS AI Lab),佛蒙特大学(Vermont)

关键词:稀疏性,正则化

CrossMatch

6. Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series

大会论文链接https://icml.cc/virtual/2023/poster/24132

PMLR链接https://proceedings.mlr.press/v202/raghu23a.html

代码https://github.com/aniruddhraghu/smd-ssl

作者:Aniruddh Raghu · Payal Chandak · Ridwan Alam · John Guttag · Collin Stultz

机构:MIT,哈佛-麻省理工健康科学技术项目(HST)

关键词:自监督、临床时序

SMD SSL

7. SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series

大会论文链接https://icml.cc/virtual/2023/poster/24856

PMLR链接https://proceedings.mlr.press/v202/huijben23a.html

代码:https://github.com/IamHuijben/SOM-CPC

作者:SeungHyun Kim · Hyunsu Kim · EungGu Yun · Hwangrae Lee · Jaehun Lee · Juho Lee

机构:埃因霍芬理工大学(tue),Onera Health,Sleep Medicine Center Kempenhaeghe

关键词:无监督,对比学习,高频时序

SOM-CPC

8. Prototype-oriented unsupervised anomaly detection for multivariate time series

大会论文链接https://icml.cc/virtual/2023/poster/24139

PMLR链接https://proceedings.mlr.press/v202/li23d.html

代码https://github.com/LiYuxin321/PUAD

作者:yuxin li · Wenchao Chen · Bo Chen · Dongsheng Wang · Long Tian · Mingyuan Zhou

机构:西安电子科技大学,德克萨斯大学奥斯汀分校(utexas)

关键词:异常检测,多元时序,无监督

PUAD

9. Learning Deep Time-index Models for Time Series Forecasting

大会论文链接https://icml.cc/virtual/2023/poster/24424

PMLR链接https://proceedings.mlr.press/v202/woo23b.html

代码https://github.com/salesforce/DeepTime

作者:Gerald Woo · Chenghao Liu · Doyen Sahoo · Akshat Kumar · Steven Hoi

机构:Salesforce,新加坡管理大学(SMU)

关键词:时间序列预测,元学习

DeepTime

10. [Oral]Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series

大会论文链接https://icml.cc/virtual/2023/poster/24923

PMLR链接https://proceedings.mlr.press/v202/ansari23a.html

代码https://github.com/clear-nus/NCDSSM

作者:Abdul Fatir Ansari · Alvin Heng · Andre Lim · Harold Soh

关键词:不规则采样时间序列

NCDSSM

11. [Oral]Self-Interpretable Time Series Prediction with Counterfactual Explanations

大会论文链接https://icml.cc/virtual/2023/poster/23975

PMLR链接https://proceedings.mlr.press/v202/yan23d.html

代码https://github.com/Wang-ML-Lab/self-interpretable-time-series

作者:Jingquan Yan · Hao Wang

机构:罗格斯大学(Rutgers)

关键词:反事实,时间序列预测,可解释性

12. Learning Perturbations to Explain Time Series Predictions

大会论文链接https://icml.cc/virtual/2023/poster/24182

PMLR链接https://proceedings.mlr.press/v202/enguehard23a.html

代码https://github.com/josephenguehard/time_interpret

作者:Joseph Enguehard(独立一个作者太牛了!)

机构:Babylon Health,Skippr, 99 Milton Keynes Business Centre

关键词:可解释性,时间序列预测

time_interpret

13. Feature Programming for Multivariate Time Series Prediction

大会论文链接https://icml.cc/virtual/2023/poster/23862

PMLR链接https://proceedings.mlr.press/v202/reneau23a.html

代码https://github.com/SirAlex900/FeatureProgramming

作者:Alex Reneau · Jerry Yao-Chieh Hu · Ammar Gilani · Han Liu

机构:西北大学(Northwestern)

关键词:特征工程,多元时间序列预测

FeatureProgramming

14. Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting

大会论文链接https://icml.cc/virtual/2023/poster/24910

PMLR链接https://proceedings.mlr.press/v202/hasson23a.html

作者:Hilaf Hasson · Danielle Robinson · Yuyang Wang · Gaurav Gupta · Youngsuk Park

关键词:集成学习,时间序列预测

24910

15. Sequential Predictive Conformal Inference for Time Series

大会论文链接https://icml.cc/virtual/2023/poster/24627

PMLR链接https://proceedings.mlr.press/v202/xu23r

代码https://github.com/hamrel-cxu/SPCI-code

作者:Chen Xu · Yao Xie

机构:佐治尼亚理工学院(Gatech)

关键词:共形预测,不确定性

SPCI

16. Non-autoregressive Conditional Diffusion Models for Time Series Prediction

大会论文链接https://icml.cc/virtual/2023/poster/25084

PMLR链接https://proceedings.mlr.press/v202/shen23d.html

作者:Lifeng Shen · James Kwok

机构:香港科技大学(HKUST)

关键词:扩散模型,时间序列预测

TimeDiff

17. Sequential Monte Carlo Learning for Time Series Structure Discovery

大会论文链接https://icml.cc/virtual/2023/poster/24520

PMLR链接https://proceedings.mlr.press/v202/saad23a.html

代码https://github.com/probsys/AutoGP.jl(代码语言是Julia)

项目地址https://probsys.github.io/AutoGP.jl/stable/

作者:Feras Saad · Brian Patton · Matthew Hoffman · Rif Saurous · Vikash Mansinghka

机构:卡耐基梅隆大学(CMU),Google,MIT

关键词:蒙特卡洛方法,高斯过程,时间序列结构发现

AutoGP

18. Domain Adaptation for Time Series Under Feature and Label Shifts

大会论文链接https://icml.cc/virtual/2023/poster/23456

PMLR链接https://proceedings.mlr.press/v202/he23b.html

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

作者:Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, Marinka Zitnik

机构:哈佛大学(Harvard),MIT林肯实验室,

关键词:域适应,标签偏移,数据偏移,分布偏移

Raincoat

时空数据(spatial-temporal data)

时空的论文偏少,且3篇内容差异较大,就不显示词云了

19. NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition

大会论文链接https://icml.cc/virtual/2023/poster/23962

PMLR链接https://proceedings.mlr.press/v202/huang23m.html

作者:Xinquan Huang · Wenlei Shi · Qi Meng · Yue Wang · Xiaotian Gao · Jia Zhang · Tie-Yan Liu

机构:阿卜杜拉国王科技大学(KAUST),微软亚洲研究院(MSRA)

关键词:神经偏微分方程,时空分解,AI4Science

20. Spatial Implicit Neural Representations for Global-Scale Species Mapping

大会论文链接https://icml.cc/virtual/2023/poster/23767

PMLR链接https://proceedings.mlr.press/v202/cole23a.html

代码https://github.com/elijahcole/sinr

作者:Elijah Cole · Grant Horn · Christian Lange · Alexander Shepard · Patrick Leary · Pietro Perona · Scott Loarie · Oisin Mac Aodha

机构:加州理工学院(CalTech),康奈尔大学(Cornell),爱丁堡大学(Edinburgh),iNaturalist

关键词:地理信息,稀疏性,隐式神经表示

sinr

21. Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation

(可能是最像时空数据挖掘的一篇了)

大会论文链接https://icml.cc/virtual/2023/poster/24346

PMLR链接https://proceedings.mlr.press/v202/zhang23p.html

代码https://github.com/HKUDS/GraphST

作者:Qianru Zhang · Chao Huang · Lianghao Xia · Zheng Wang · Siu Ming Yiu · Ruihua Han

机构:香港大学(HKU),南洋理工大学(NTU)

关键词:时空图预测、对比学习,图表示学习

GraphST

相关链接

ICML2023接受论文https://icml.cc/virtual/2023/papers.html

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目录
  • 时间序列(time series)
    • 1. Probabilistic Imputation for Time-series Classification with Missing Data
    • 2. Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
    • 3. Deep Latent State Space Models for Time-Series Generation
    • 4. Neural Stochastic Differential Games for Time-series Analysis
    • 5. Context Consistency Regularization for Label Sparsity in Time Series
    • 6. Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series
    • 7. SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series
    • 8. Prototype-oriented unsupervised anomaly detection for multivariate time series
    • 9. Learning Deep Time-index Models for Time Series Forecasting
    • 10. [Oral]Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
    • 11. [Oral]Self-Interpretable Time Series Prediction with Counterfactual Explanations
    • 12. Learning Perturbations to Explain Time Series Predictions
    • 13. Feature Programming for Multivariate Time Series Prediction
    • 14. Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
    • 15. Sequential Predictive Conformal Inference for Time Series
    • 16. Non-autoregressive Conditional Diffusion Models for Time Series Prediction
    • 17. Sequential Monte Carlo Learning for Time Series Structure Discovery
    • 18. Domain Adaptation for Time Series Under Feature and Label Shifts
  • 时空数据(spatial-temporal data)
    • 19. NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition
    • 20. Spatial Implicit Neural Representations for Global-Scale Species Mapping
    • 21. Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation
  • 相关链接
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