ICML 2025 | 时间序列(Time Series)论文总结

ICML 2025将在2025年7月13日至7月19日（周六）在温哥华会议中心举行，本文总结了ICML 2025有关时间序列(Time Series)相关文章，共计63篇。

时间序列Topic：预测，分类，异常检测，生成，因果发现，基础模型，大语言模型等。如有疏漏，欢迎补充！

如果论文中附图，则论文已经在网络上公开（arXiv，Openreview等）

1. Patch-wise Structural Loss for Time Series Forecasting
2. TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation
3. BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimisation and Diffusion Modelling
4. Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time Series
5. HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
6. LSCD: Lomb–Scargle Conditioned Diffusion for Irregular Time series Imputation
7. LETS Forecast: Learning Embedology for Time Series Forecasting
8. TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting
9. Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer
10. When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series
11. TransPL: Pseudo-Labeling via Code Transitions for Time Series Adaptation
12. Channel Normalization for Time Series Channel Identification
13. Slimming the Fat-Tail: MoF for Adaptive Time Series Modeling
14. Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
15. CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations
16. Exploring Representations and Interventions in Time Series Foundation Models
17. CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp Modeling
18. Causal Discovery from Conditionally Stationary Time Series
19. TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting
20. AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
21. TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
22. TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
23. A Non-isotropic Time Series Diffusion Model with Moving Average Transitions
24. Spectral-Aware Reservoir Computing for Fast and Accurate Time Series Classification
25. Time Series Representations with Hard-Coded Invariances
26. Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
27. Non-stationary Diffusion For Probabilistic Time Series Forecasting
28. $K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
29. LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
30. Shifting time: Time-series forecasting with Khatri-Rao neural operators
31. Optimal Information Retention for Time-Series Explanations
32. Lightweight Online Adaption for Time Series Foundation Model Forecasts
33. Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
34. Retrieval Augmented Time Series Forecasting
35. IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
36. Relational Conformal Prediction for Correlated Time Series
37. In-Context Fine-Tuning for Time-Series Foundation Models
38. FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting
39. A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle
40. Temporal Query Network for Efficient Multivariate Time Series Forecasting
41. TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
42. LightGTS: A Lightweight General Time Series Forecasting Model
43. Efficient Time Series Processing for Transformers and State-Space Models through Token Merging
44. SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
45. Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series
46. LAST SToP for Modeling Asynchronous Time Series
47. WAVE: Weighted Autoregressive Varing Gate for Time Series Forecasting
48. KAN-AD: Time Series Anomaly Detection with Kolmogorov–Arnold Networks
49. Sundial: A Family of Highly Capable Time Series Foundation Models
50. KoNODE: Koopman-Driven Neural Ordinary Differential Equations with Evolving Parameters for Time Series Analysis
51. ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset
52. FIC-TSC: Learning Time Series Classification with Fisher Information Constraint
53. Learning Soft Sparse Shapes for Efficient Time-Series Classification
54. VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
55. Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
56. Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
57. VerbalTS: Generating Time Series from Texts
58. TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
59. Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization
60. Empowering Time Series Foundation Models with Sparse Mixture of Experts
61. Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly Detection
62. Timing: Temporality-Aware Integrated Gradients for Time Series Explanation
63. Arrow: Accelerator for Time Series Causal Discovery with Time Weaving

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1 TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation

链接：https://icml.cc/virtual/2025/poster/43701

作者：Daoyu Wang, Mingyue Cheng, Zhiding Liu, Qi Liu

关键词：预测，自回归，自监督，

2 Time Series Representations with Hard-Coded Invariances

链接：https://icml.cc/virtual/2025/poster/45216

作者：Thibaut Germain, Chrysoula Kosma, Laurent Oudre

关键词：表示学习，不变性，卷积

3 Exploring Representations and Interventions in Time Series Foundation Models

链接：https://icml.cc/virtual/2025/poster/44453

作者：Michal Wilinski, Mononito Goswami, Nina Żukowska, Willa Potosnak, Artur Dubrawski

关键词：基础模型，表示学习

4 Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer

链接：https://icml.cc/virtual/2025/poster/46383

作者：Yihang Wang, Yuying Qiu, Peng Chen, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

关键词：预测，少样本，零样本

5 TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/46502

作者：Yifan Hu, Guibin Zhang, Peiyuan Liu, Disen Lan, Naiqi Li, Dawei Cheng, Tao Dai, Shutao Xia, Shirui Pan

关键词：预测，时空图，通道关系

6 Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

链接：https://icml.cc/virtual/2025/poster/46131

作者：Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang, Christos Faloutsos, Michael Mahoney, Andrew Wilson, Youngsuk Park, Syama Sundar Yadav Rangapuram, Danielle Maddix, Yuyang Wang

关键词：预测，基础模型，小波变换，token化

7 Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44762

作者：Siru Zhong, Weilin Ruan, Ming Jin, Huan Li, Qingsong Wen, Yuxuan Liang

关键词：预测，多模态，视觉语言模型

8 Lightweight Online Adaption for Time Series Foundation Model Forecasts

链接：https://icml.cc/virtual/2025/poster/44485

作者：Thomas Lee, William Toner, Rajkarn Singh, Artjom Joosen, Martin Asenov

关键词：预测，基础模型，在线学习

9 When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series

链接：https://icml.cc/virtual/2025/poster/45978

作者：Min-Yeong Park, Won-Jeong Lee, Seong Tae Kim, Gyeong-Moon Park

关键词：异常检测，提示

10 TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/46428

作者：Qinglong Liu, Cong Xu, Wenhao Jiang, Kaixuan Wang, Lin Ma, Haifeng Li

关键词：预测，非平稳性，多尺度

11 AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/43518

作者：Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo, Albert Thomas, Maurizio Filippone, Balázs Kégl

关键词：预测，基础模型，单变量，概率预测

12 TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state

链接：https://icml.cc/virtual/2025/poster/43851

作者：Xiaowen Ma, Zhen-Liang Ni, Shuai Xiao, Xinghao Chen

关键词：长时预测，变量感知，时间感知

13 Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/43827

作者：Zhining Liu, Ze Yang, Xiao Lin, Ruizhong Qiu, Tianxin Wei, Yada Zhu, Hendrik Hamann, Jingrui He, Hanghang Tong

关键词：预测，自适应

14 TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/43973

作者：Peiyuan Liu, Beiliang Wu, Yifan Hu, Naiqi Li, Tao Dai, Jigang Bao, Shutao Xia

关键词：长时预测，非平稳性

15 HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/43741

作者：Boyuan Li, Yicheng Luo, Zhen Liu, Junhao Zheng, Jianming Lv, Qianli Ma

关键词：预测，超图，不规则多元时序

16 LETS Forecast: Learning Embedology for Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/45595

作者：Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV, Nada Elkordi, Yin Li

关键词：预测，经验动态建模

17 Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44722

作者：Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann

关键词：预测，差分隐私

18 TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/45815

作者：Qihe Huang, Zhengyang Zhou, Kuo Yang, Zhongchao Yi, Xu Wang, Yang Wang

关键词：预测，极简主义，高效性

19 CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp Modeling

链接：https://icml.cc/virtual/2025/poster/44425

作者：Feifei Kou, Jiahao Wang, Lei Shi, Yuhan Yao, Yawen Li, Suguo Zhu, Zhongbao Zhang, Junping Du

关键词：预测，时间戳建模，跨频交互

20 Winner-takes-all for Multivariate Probabilistic Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/46485

作者：Adrien Cortes, Remi Rehm, Victor Letzelter

关键词：预测，多元概率预测

21 Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44243

作者：RISHI JINKA, Venkata Sai Mothish Gonugunta, Deepak N. Subramani

关键词：预测，非线性变换，条件扩散模型

22 Patch-wise Structural Loss for Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44030

作者：Dilfira Kudrat, Zongxia Xie, Yanru Sun, Tianyu Jia, Qinghua Hu

关键词：预测，结构化损失

23 FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44031

作者：Yue Jiang, Yile Chen, Xiucheng Li, Qin Chao, SHUAI LIU, Gao Cong

关键词：预测，少样本，时空大模型

24 Non-stationary Diffusion For Probabilistic Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44783

作者：Weiwei Ye, Zhuopeng Xu, Ning Gui

关键词：预测，概率预测，非平稳

25 VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/46346

作者：Xingjian Wu, Xiangfei Qiu, Hongfan Gao, Jilin Hu, Chenjuan Guo, Bin Yang

关键词：概率预测，变分自编码器，库普曼，卡尔曼

26 Shifting time: Time-series forecasting with Khatri-Rao neural operators

链接：https://icml.cc/virtual/2025/poster/44565

作者：Srinath Dama, Kevin L Course, Prasanth B Nair

关键词：时间序列建模、时空建模、时移算子、Khatri-Rao 神经算子、神经算子、算子学习

27 LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization

链接：https://icml.cc/virtual/2025/poster/45059

作者：Wenzhe Niu, Zongxia Xie, Yanru Sun, Wei He, Man Xu, Chao Hao

关键词：预测，语言模型，近端策略优化（PPO）

28 Retrieval Augmented Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/45826

作者：Sungwon Han, Seungeon Lee, MEEYOUNG CHA, Sercan Arik, Jinsung Yoon

关键词：预测，检索增强（RAG）

29 Temporal Query Network for Efficient Multivariate Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44603

作者：Shengsheng Lin, Haojun Chen, Haijie Wu, Chunyun Qiu, Weiwei Lin

关键词：预测，时间查询，多元时间序列预测

30 A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle

链接：https://icml.cc/virtual/2025/poster/44262

作者：Yu Chen, Nathalia Céspedes, Payam Barnaghi

关键词：预测，Transformer

31 LightGTS: A Lightweight General Time Series Forecasting Model

链接：https://icml.cc/virtual/2025/poster/44879

作者：Yihang Wang, Yuying Qiu, Peng Chen, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

关键词：预测，轻量化

32 SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting

链接：https://icml.cc/virtual/2025/poster/44949

作者：Yitian Zhang, Liheng Ma, Antonios Valkanas, Boris Oreshkin, Mark Coates

关键词：预测，库普曼算子

33 WAVE: Weighted Autoregressive Varing Gate for Time Series Forecasting

链接：https://icml.cc/virtual/2025/poster/45318

作者：Jiecheng Lu, Xu Han, Yan Sun, Shihao Yang

关键词：预测，自回归

34 VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters

链接：https://icml.cc/virtual/2025/poster/46441

作者：Mouxiang Chen, Lefei Shen, Zhuo Li, Xiaoyun Wang, Jianling Sun, Chenghao Liu

关键词：预测，多模态

35 Causality-Aware Contrastive Learning for Robust Multivariate Time-Series Anomaly Detection

链接：https://icml.cc/virtual/2025/poster/45960

作者：HyunGi Kim, Jisoo Mok, Dong Jun Lee, Jaihyun Lew, Sungjae Sungjae, Sungroh Yoon

关键词：异常检测，因果感知

36 KAN-AD: Time Series Anomaly Detection with Kolmogorov–Arnold Networks

链接：https://icml.cc/virtual/2025/poster/45584

作者：Quan Zhou, Changhua Pei, Fei Sun, Jianhui LI, haiming zhang, Gaogang Xie, Dan Pei, Zhengwei Gao, HanJing

关键词：异常检测，KAN

37 Learning Soft Sparse Shapes for Efficient Time-Series Classification

链接：https://icml.cc/virtual/2025/poster/46130

作者：Zhen Liu, Yicheng Luo, Boyuan Li, Emadeldeen Eldele, Min Wu, Qianli Ma

关键词：分类，高效性

38 FIC-TSC: Learning Time Series Classification with Fisher Information Constraint

链接：https://icml.cc/virtual/2025/poster/45977

作者：Xiwen Chen, Wenhui Zhu, Peijie Qiu, Hao Wang, Huayu Li, ZIHAN LI, Yalin Wang, Aristeidis Sotiras, Abolfazl Razi

关键词：分类

39 Spectral-Aware Reservoir Computing for Fast and Accurate Time Series Classification

链接：https://icml.cc/virtual/2025/poster/45987

作者：Shikang Liu, Chuyang Wei, Xiren Zhou, Huanhuan Chen

关键词：分类，谱感知

40 Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series

链接：https://icml.cc/virtual/2025/poster/45009

作者：Zachary Brown, David Carlson

关键词：因果图

41 Causal Discovery from Conditionally Stationary Time Series

链接：https://icml.cc/virtual/2025/poster/44317

作者：Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra, Ruibo Tu, Gabriele Schweikert, Hedvig Kjellström, Yingzhen Li

关键词：因果发现，平稳时间序列

42 Arrow: Accelerator for Time Series Causal Discovery with Time Weaving

链接：https://icml.cc/virtual/2025/poster/46084

作者：YUANYUAN YAO, Yuan Dong, Lu Chen, Kun Kuang, Ziquan Fang, Cheng Long, Yunjun Gao, TIANYI LI

关键词：因果发现

43 KoNODE: Koopman-Driven Neural Ordinary Differential Equations with Evolving Parameters for Time Series Analysis

链接：https://icml.cc/virtual/2025/poster/45804

作者：Hanru Bai, Weiyang Ding

关键词：时间序列分析，库普曼理论

44 TransPL: Pseudo-Labeling via Code Transitions for Time Series Adaptation

链接：https://icml.cc/virtual/2025/poster/46696

作者：Jaeho Kim, Seulki Lee

关键词：时间序列自适应

45 Efficient Time Series Processing for Transformers and State-Space Models through Token Merging

链接：https://icml.cc/virtual/2025/poster/44933

作者：Leon Götz, Marcel Kollovieh, Stephan Günnemann, Leo Schwinn

关键词：时间序列处理加速，token化，状态空间模型

46 A Non-isotropic Time Series Diffusion Model with Moving Average Transitions

链接：https://icml.cc/virtual/2025/poster/43547

作者：Chenxi Wang, Linxiao Yang, Zhixian Wang, Liang Sun, Yi Wang

47 LAST SToP for Modeling Asynchronous Time Series

链接：https://icml.cc/virtual/2025/poster/45155

作者：Shubham Gupta, Thibaut Durand, Graham Taylor, Lilian Bialokozowicz

关键词：异步时间序列，大模型

48 Slimming the Fat-Tail: MoF for Adaptive Time Series Modeling

链接：https://icml.cc/virtual/2025/poster/44444

作者：Tianyu Liu, kai sun, Fuchun Sun, Yu Luo, Yuanlong Zhang

关键词：时间序列建模，变形流

49 In-Context Fine-Tuning for Time-Series Foundation Models

链接：https://icml.cc/virtual/2025/poster/43707

作者：Matthew Faw, Rajat Sen, Yichen Zhou, Abhimanyu Das

50 Sundial: A Family of Highly Capable Time Series Foundation Models

链接：https://icml.cc/virtual/2025/poster/45591

作者：Yong Liu, Guo Qin, Zhiyuan Shi, Zhi Chen, Caiyin Yang, Xiangdong Huang, Jianmin Wang, Mingsheng Long

关键词：基础模型，多任务

51 ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset

链接：https://icml.cc/virtual/2025/poster/45847

作者：Yilin Wang, Peixuan Lei, chen tao, Jie Song, Haoyuzhe, Yuxuan Zhang, LEI JIA, Yuanxiang Li, Zhongyu Wei

关键词：多模态问答，多任务

52 TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning

链接：https://icml.cc/virtual/2025/poster/44741

作者：Ron Shapira Weber, shahar benishay, Shahaf E. Finder, Andrey Lavrinenko, Oren Freifeld

关键词：对齐，自监督

53 Channel Normalization for Time Series Channel Identification

链接：https://icml.cc/virtual/2025/poster/45365

作者：Seunghan Lee, Taeyoung Park, Kibok Lee

关键词：通道归一化，通道验证

54 CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlations

链接：https://icml.cc/virtual/2025/poster/44558

作者：Haotian Si, Changhua Pei, Dan Pei, Gaogang Xie, Jianhui LI

关键词：预测，分块空间

55 LSCD: Lomb–Scargle Conditioned Diffusion for Irregular Time series Imputation

链接：https://icml.cc/virtual/2025/poster/45821

作者：Elizabeth M Fons Etcheverry, Alejandro Sztrajman, Yousef El-Laham, Luciana Ferrer, Svitlana Vyetrenko, Manuela Veloso

关键词：插补，不规则时间序列，扩散

56 VerbalTS: Generating Time Series from Texts

链接：https://icml.cc/virtual/2025/poster/45631

作者：Shuqi Gu, Chuyue Li, Baoyu Jing, Kan Ren

关键词：时间序列生成，文本数据

57 Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time Series

链接：https://icml.cc/virtual/2025/poster/44115

作者：Yicheng Luo, Bowen Zhang, Zhen Liu, Qianli Ma

关键词：不规则时间序列，图神经网络

58 BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimisation and Diffusion Modelling

链接：https://icml.cc/virtual/2025/poster/43728

作者：Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Renhe Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian

59 Empowering Time Series Foundation Models with Sparse Mixture of Experts

链接：https://icml.cc/virtual/2025/poster/45201

作者：Xu Liu, Juncheng Liu, Gerald Woo, Taha Aksu, Yuxuan Liang, Roger Zimmermann, Chenghao Liu, Junnan Li, Silvio Savarese, Caiming Xiong, Doyen Sahoo

关键词:时间序列基础模型，混合专家系统

60 Optimal Information Retention for Time-Series Explanations

链接：https://icml.cc/virtual/2025/poster/43746

作者：Jinghang Yue, Jing Wang, Lu Zhang, Shuo Zhang, Da Li, Zhaoyang Ma, Youfang Lin

关键词：最优信息保留原则，可解释性

61 Timing: Temporality-Aware Integrated Gradients for Time Series Explanation

链接：https://icml.cc/virtual/2025/poster/43941

作者：Hyeongwon Jang, Changhun Kim, Eunho Yang

关键词：可解释性，积分梯度

62 IMTS is Worth Time Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction

链接：https://icml.cc/virtual/2025/poster/46570

作者：Zhangyi Hu, Jiemin Wu, Hua XU, Mingqian Liao, Ninghui Feng, Bo Gao, Songning Lai, Yutao Yue

关键词：预测，不规则时间序列

63 Relational Conformal Prediction for Correlated Time Series

链接：https://icml.cc/virtual/2025/poster/43601

作者：Andrea Cini, Alexander Jenkins, Danilo Mandic, Cesare Alippi, Filippo Maria Bianchi

关键词：共形预测，关联时间序列

词**：可解释性，积分梯度

62 IMTS is Worth Time Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction

链接：https://icml.cc/virtual/2025/poster/46570

作者：Zhangyi Hu, Jiemin Wu, Hua XU, Mingqian Liao, Ninghui Feng, Bo Gao, Songning Lai, Yutao Yue

关键词：预测，不规则时间序列

63 Relational Conformal Prediction for Correlated Time Series

链接：https://icml.cc/virtual/2025/poster/43601

作者：Andrea Cini, Alexander Jenkins, Danilo Mandic, Cesare Alippi, Filippo Maria Bianchi

关键词：共形预测，关联时间序列

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