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 221 篇,第 2 / 5 页
- NeurIPS 2025Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning
- NeurIPS 2025DynaGuide: Steering Diffusion Polices with Active Dynamic Guidance
- NeurIPS 2025Dynamical modeling of nonlinear latent factors in multiscale neural activity with real-time inference
- NeurIPS 2025EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
- NeurIPS 2025Enhancing the Maximum Effective Window for Long-Term Time Series Forecasting
- NeurIPS 2025Entropic Time Schedulers for Generative Diffusion Models
- NeurIPS 2025Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces
- NeurIPS 2025Every Rollout Counts: Optimal Resource Allocation for Efficient Test-Time Scaling
- NeurIPS 2025EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
- NeurIPS 2025Exact Expressive Power of Transformers with Padding
- NeurIPS 2025Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data
- NeurIPS 2025Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos
- NeurIPS 2025FEEL: Quantifying Heterogeneity in Physiological Signals for Generalizable Emotion Recognition
- NeurIPS 2025Finite Sample Analyses for Continuous-time Linear Systems: System Identification and Online Control
- NeurIPS 2025Finite-Time Analysis of Stochastic Nonconvex Nonsmooth Optimization on the Riemannian Manifolds
- NeurIPS 2025Finite-Time Bounds for Average-Reward Fitted Q-Iteration
- NeurIPS 2025Flow based approach for Dynamic Temporal Causal models with non-Gaussian or Heteroscedastic Noises
- NeurIPS 2025Forecasting in Offline Reinforcement Learning for Non-stationary Environments
- NeurIPS 2025Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generation
- NeurIPS 2025Fortifying Time Series: DTW-Certified Robust Anomaly Detection
- NeurIPS 2025Fractional Langevin Dynamics for Combinatorial Optimization via Polynomial-Time Escape
- NeurIPS 2025From Indicators to Insights: Diversity-Optimized for Medical Series-Text Decoding via LLMs
- NeurIPS 2025Functional Virtual Adversarial Training for Semi-Supervised Time Series Classification
- NeurIPS 2025GEM: Empowering MLLM for Grounded ECG Understanding with Time Series and Images
- NeurIPS 2025Generating Multi-Table Time Series EHR from Latent Space with Minimal Preprocessing
- NeurIPS 2025Glocal Information Bottleneck for Time Series Imputation
- NeurIPS 2025Gradient-Weight Alignment as a Train-Time Proxy for Generalization in Classification Tasks
- NeurIPS 2025GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding
- NeurIPS 2025Hamiltonian Descent Algorithms for Optimization: Accelerated Rates via Randomized Integration Time
- NeurIPS 2025Heavy-Ball Momentum Method in Continuous Time and Discretization Error Analysis
- NeurIPS 2025High Dynamic Range Imaging with Time-Encoding Spike Camera
- NeurIPS 2025How Different from the Past? Spatio-Temporal Time Series Forecasting with Self-Supervised Deviation Learning
- NeurIPS 2025How Patterns Dictate Learnability in Sequential Data
- NeurIPS 2025Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning
- NeurIPS 2025Improving Time Series Forecasting via Instance-aware Post-hoc Revision
- NeurIPS 2025Inference-time Alignment in Continuous Space
- NeurIPS 2025Inference-Time Hyper-Scaling with KV Cache Compression
- NeurIPS 2025Inference-Time Personalized Alignment with a Few User Preference Queries
- NeurIPS 2025Investigating Hallucinations of Time Series Foundation Models through Signal Subspace Analysis
- NeurIPS 2025Kernel Density Steering: Inference-Time Scaling via Mode Seeking for Image Restoration
- NeurIPS 2025Kinetics: Rethinking Test-Time Scaling Law
- NeurIPS 2025Know What You Don't Know: Uncertainty Calibration of Process Reward Models
- NeurIPS 2025Learnable Burst-Encodable Time-of-Flight Imaging for High-Fidelity Long-Distance Depth Sensing
- NeurIPS 2025Learning Linear Attention in Polynomial Time
- NeurIPS 2025Learning long range dependencies through time reversal symmetry breaking
- NeurIPS 2025Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift
- NeurIPS 2025Learning with Calibration: Exploring Test-Time Computing of Spatio-Temporal Forecasting
- NeurIPS 2025Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projections
- NeurIPS 2025Less but More: Linear Adaptive Graph Learning Empowering Spatiotemporal Forecasting
- NeurIPS 2025Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning
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。