时间序列论文趋势 2023–2026

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。

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 424 篇，第 9 / 9 页

401. NeurIPS 2024The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark
402. NeurIPS 2024The Fine-Grained Complexity of Gradient Computation for Training Large Language Models
403. NeurIPS 2024Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences
404. NeurIPS 2024Time-Constrained Robust MDPs
405. NeurIPS 2024Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
406. NeurIPS 2024Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis
407. NeurIPS 2024Time-Reversal Provides Unsupervised Feedback to LLMs
408. NeurIPS 2024TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
409. NeurIPS 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
410. NeurIPS 2024TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices
411. NeurIPS 2024Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms
412. NeurIPS 2024Towards Editing Time Series
413. NeurIPS 2024Towards Understanding Evolving Patterns in Sequential Data
414. NeurIPS 2024TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation
415. NeurIPS 2024Trajectory Flow Matching with Applications to Clinical Time Series Modelling
416. NeurIPS 2024Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
417. NeurIPS 2024TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
418. NeurIPS 2024UniMTS: Unified Pre-training for Motion Time Series
419. NeurIPS 2024UniTS: A Unified Multi-Task Time Series Model
420. NeurIPS 2024Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
421. NeurIPS 2024Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series
422. NeurIPS 2024When are dynamical systems learned from time series data statistically accurate?
423. NeurIPS 2024When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
424. NeurIPS 2024YOLOv10: Real-Time End-to-End Object Detection

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。