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 599 篇,第 2 / 12 页
- ICML 2026DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables
- ICML 2026DecodeShare: Tracing the Shared Subspace of LLM Decode-Time Decisions
- ICML 2026Decoupling Universal Laws and Environmental Heterogeneity: A Physics-Inspired Framework for Robust Spatio-Temporal Forecasting
- ICML 2026DeepBlip: Estimating Conditional Average Treatment Effects Over Time
- ICML 2026Delving into Non-Exchangeability for Conformal Prediction in Graph-Structured Multivariate Time Series
- ICML 2026Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling
- ICML 2026Denoising without Diffusion: Fixed-Noise Denoiser Anomaly Detection in Tabular Data
- ICML 2026Diff-MN: Diffusion Parameterized MoE-NCDE for Continuous Time Series Generation with Irregular Observations
- ICML 2026Discriminative Visual Process Rewards for Scaling Thinking at Test-Time with Images
- ICML 2026DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Prediction
- ICML 2026Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
- ICML 2026DITING: A Weak Degradation Listener for Battery Lifetime Early Prediction
- ICML 2026Divide and Contrast: Learning Robust Temporal Features without Augmentation
- ICML 2026DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes
- ICML 2026DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting
- ICML 2026DSENet: A Novel Dual-Stream Enhancement Network for Multi-Scale Non-Stationary Time Series Forecasting
- ICML 2026DualTimesField: Rethinking Time Series as Continuous-Time Trends and Events
- ICML 2026Dynamic Compression Flows for Neuroscience Data
- ICML 2026Dynamic Fractal Mamba: A Neural Renormalization Group Flow for Scale-Invariant Sequence Modeling
- ICML 2026Dynamic Relational Priming Improves Transformer in Multivariate Time Series
- ICML 2026Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting
- ICML 2026Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
- ICML 2026ECHO: Entropy-Confidence Hybrid Optimization for Test-Time Reinforcement Learning
- ICML 2026Efficient Learning of Deep State Space Models via Importance Smoothing
- ICML 2026Efficient Neural Controlled Differential Equations via Attentive Kernel Smoothing
- ICML 2026Ellipsoidal Time Series Forecasting
- ICML 2026Empirical Gaussian Processes
- ICML 2026Escaping the Verifier: Learning to Reason via Demonstrations
- ICML 2026ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment
- ICML 2026Evolving Quantitative Reasoning through Self-Play in Digital Twin Markets
- ICML 2026Expanding the Chaos: Neural Operator for Stochastic (Partial) Differential Equations
- ICML 2026Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attacks
- ICML 2026Extending Prediction-Powered Inference through Conformal Prediction
- ICML 2026FedPAT: Federated Test-Time Adaptation via Prototype Affinity Topology
- ICML 2026Finite-time Convergence Analysis of Actor-Critic with Evolving Reward
- ICML 2026FIPN: Forward Self-Organizing Interpretable Polynomial Networks for Time Series Forecasting
- ICML 2026Flow Equivariant World Models: Structured Memory for Dynamic Environments
- ICML 2026FlowState: Sampling-Rate‑Equivariant Time‑Series Forecasting
- ICML 2026Forward-Chaining Temporal Point Process
- ICML 2026From geometry to dynamics: Learning overdamped Langevin dynamics from sparse observations with geometric constraints
- ICML 2026From Observations to States: Latent Time Series Forecasting
- ICML 2026From Teacher Pathways to Invariant Manifolds: Consensus Subspace Distillation for TSFMs
- ICML 2026From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Space
- ICML 2026Front-Loaded Robust Conformal Prediction: Heavy Calibration, Minimal Test-Time Cost
- ICML 2026Function-Valued Causal Influence in Nonlinear Time Series
- ICML 2026FUSE: Ensembling Verifiers with Zero Labeled Data
- ICML 2026Future-Gain Guided Test-Time Learning for Large Language Models
- ICML 2026GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function
- ICML 2026Generalizing Multi-Scale Time-Series Modeling with a Single Operator
- ICML 2026Generative Modeling of Irregular Time Series via SDE-Induced Continuous-Discrete Variational Inference
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。