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 2,156 篇,第 11 / 44 页
- ICML 2026Ranking Time Series using a Time Warping Ideal Point Model
- ICML 2026Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning
- ICML 2026RealtimeTool: Parallel Decoding for Real-Time LLM Function Calling
- ICML 2026ReAugment: Targeted Few-Shot Time Series Augmentation via Model Zoo-Guided Reinforcement Learning
- ICML 2026ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters
- ICML 2026Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting
- ICML 2026Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
- ICML 2026Rethinking Multimodal Time-Series Forecasting Evaluation
- ICML 2026Rethinking Time-Series Imputation as Conditional Inference along Temporal Evolution
- ICML 2026Revealing Scaling Paradox in Large-scale Time Series Models: Implications for More Efficient and Accurate Forecasting
- ICML 2026Revisiting Neural Processes via Fourier Transform and Volterra Series
- ICML 2026Reviving Error Correction in Modern Deep Time-Series Forecasting
- ICML 2026Robust Causal Discovery in Real-World Time Series with Power-Laws
- ICML 2026Robust Inter-Series Dependency Modeling for Time Series Forecasting via Information-Theoretic Alignment
- ICML 2026Robustifying Vision-Language Models via Test-Time Prompt Adaptation
- ICML 2026RTInfer: Real-Time Inference of Multiple DNNs on Edge GPUs
- ICML 2026SafeCompass: Dynamic Chain-of-Thought Steering via Inference-Time Safety Signals
- ICML 2026Sampling from Your Language Model One Byte at a Time
- ICML 2026See More, Forecast Better and Faster: Enhancing Time Series Foundation Models via Inference-Time Plug-and-Play Downsampling
- ICML 2026Seeking Commonality, Preserving Specificity: A Spectral-Aware Hierarchical Framework for Cross-City Road Representation Learning
- ICML 2026SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
- ICML 2026Self-Supervised Dynamical System Representations for Physiological Time-Series
- ICML 2026Shapley Regularized Neural Granger Causality
- ICML 2026Simple Approximation and Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures
- ICML 2026Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases
- ICML 2026Sparse Regression with $\ell_0$ Constraints for $\alpha$-Mixing Time Series: Algorithms and Guarantees
- ICML 2026SparseOpt: Addressing Normalization-induced Gradient Skew in Sparse Training
- ICML 2026StarEmbed: Benchmarking Time Series Foundation Models on Astronomical Observations of Variable Stars
- ICML 2026StretchTime: Adaptive Time Series Forecasting via Symplectic Attention
- ICML 2026SubspacePath Pruner: Inference-time Pruning via Probe-based Representation–Parameter Coupling
- ICML 2026SURGE: Approximation and Training Free Particle Filter for Diffusion Surrogate
- ICML 2026Taming the Recent-Data Bias: Towards Robust Time Series Forecasting with Global Context
- ICML 2026TeamWork: Multivariate Time Series Anomaly Detection via Asymmetric Role-aware Channel Modeling
- ICML 2026TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis
- ICML 2026Terminal Dimension Reduction for Time Series with Applications
- ICML 2026Test-Time Graph Search for Goal-Conditioned Reinforcement Learning
- ICML 2026Test-Time Guidance for Flow-Based Generative Models via Parallel Tempering on Source Distributions
- ICML 2026Test-Time Learning of Causal Structure from Interventional Data
- ICML 2026Test-time Offline Reinforcement Learning on Goal-related Experience
- ICML 2026Test-Time Training with KV Binding Is Secretly Linear Attention
- ICML 2026TF-FACE: Time-Frequency Fusion Learning via Frequency-Domain Adaptive and Controllable Enhancement for Trajectory Prediction
- ICML 2026TFRBench: A Reasoning Benchmark for Evaluating Forecasting Systems
- ICML 2026Theoretical Investigation on Inductive Bias of Isolation Forest
- ICML 2026ThetaEvolve: Test-time Learning on Open Problems
- ICML 2026Time Series Forecasting Through the Lens of Dynamics
- ICML 2026Time series saliency maps: Explaining models across multiple domains
- ICML 2026Time Series, Vision, and Language: Exploring the Limits of Alignment in Contrastive Representation Spaces
- ICML 2026Time-Consistent Robust Multi-Objective Reinforcement Learning via a Bellman–Isaacs Weight-Adversary Recursion
- ICML 2026Time-PEFT: Temporal and Multichannel Complexity-Based Fine-Tuning for Time-Series Foundation Models
- ICML 2026Time-Series Decomposition as a Standalone Task: A Mechanism-Driven Diagnostic Benchmark
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。