时间序列论文趋势 2023–2026
预测与异常检测
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 2,157 篇被归入该主题的论文。
主要结论
- 时间序列论文从 2023 年的 272 篇增长到 2026 年的 876 篇，三年间扩大到约 3.2 倍。
- NeurIPS 是发时间序列论文最多的会议，2023–2026 年共 757 篇，占四个会议总量的 35%。
- 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 6 篇增至 2026 年的 85 篇。
- 在「图与结构化数据」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的分子建模是 2.7 倍，时间序列是 3.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 91 | 60 | 62 | 59 | 272 |
| 2024 | 147 | 95 | 114 | 68 | 424 |
| 2025 | 221 | 131 | 159 | 74 | 585 |
| 2026 | 298 | 220 | 264 | 94 | 876 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- NeurIPS 2026A Batched Hartigan's $k$-Means Clustering
- ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
- ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
- CVPR 2026Activation Matters Test-time Activated Negative Labels for OOD Detection with
- NeurIPS 2025Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
- ICML 2025$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
- ICLR 2025A deep inverse-mapping model for a flapping robotic wing
- CVPR 2025Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and Harmonization
- NeurIPS 2024A Continuous-time Stochastic Gradient Descent Method for Continuous Data
- ICML 2024$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
- ICLR 2024ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
- CVPR 2024Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation
- NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
- ICML 2023Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time
- ICLR 2023A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
- CVPR 2023ActMAD: Activation Matching To Align Distributions for Test-Time-Training
- NeurIPS 2026A Locally Tokenized Generative Model for Robust Time-Series Watermarking
- ICML 2026ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
- ICLR 2026A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems
- CVPR 2026Continuous Exposure-Time Modeling for Realistic Atmospheric Turbulence Synthesis
全部时间序列论文
共 59 篇，第 2 / 2 页
- CVPR 2023TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation
- CVPR 2023Test Time Adaptation With Regularized Loss for Weakly Supervised Salient Object Detection
- CVPR 2023TIPI: Test Time Adaptation With Transformation Invariance
- CVPR 2023Unsupervised Space-Time Network for Temporally-Consistent Segmentation of Multiple Motions
- CVPR 2023UV Volumes for Real-Time Rendering of Editable Free-View Human Performance
- CVPR 2023ViTs for SITS: Vision Transformers for Satellite Image Time Series
- CVPR 2023VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking
- CVPR 2023YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors
- CVPR 2023You Only Segment Once: Towards Real-Time Panoptic Segmentation
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查时间序列在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "time-series"}
常见问题
- 2023–2026 年四大会议一共有多少篇时间序列论文？
- 共 2,157 篇，按年份分别是 2023 年 272 篇、2024 年 424 篇、2025 年 585 篇、2026 年 876 篇。
- NeurIPS 2026 有多少篇时间序列论文？
- NeurIPS 2026 有 298 篇时间序列论文，上一届是 221 篇。
- ICLR 2026 有多少篇时间序列论文？
- ICLR 2026 有 220 篇时间序列论文，上一届是 131 篇。
- ICML 2026 有多少篇时间序列论文？
- ICML 2026 有 264 篇时间序列论文，上一届是 159 篇。
- CVPR 2026 有多少篇时间序列论文？
- CVPR 2026 有 94 篇时间序列论文，上一届是 74 篇。
- 哪个会议的时间序列论文最多？
- NeurIPS，2023–2026 年共 757 篇。