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 298 篇,第 4 / 6 页
- NeurIPS 2026Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
- NeurIPS 2026Neural Fractional Stochastic Differential Equations
- NeurIPS 2026Neural Neural Scaling Laws
- NeurIPS 2026Neural Optimal Transport in Hilbert Spaces
- NeurIPS 2026Neurosymbolic Learning for Inference-Time Argumentation
- NeurIPS 2026NOCE-Net: Representation Learning for Battery Operational Context via Nested Sequence Modelling
- NeurIPS 2026NPUsper: Eliminating Redundant Computation for Real-Time Whisper on Mobile NPUs
- NeurIPS 2026OATS: Online Data Augmentation for Time Series Foundation Models
- NeurIPS 2026Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
- NeurIPS 2026Observations Drift, Structures Remain: Structural Pretraining with Time Alignment for Electromagnetic Signals
- NeurIPS 2026ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow
- NeurIPS 2026OHATP: Graph Anomaly Detection with Orthogonal-Hyperspherical Augmentation and Topology Perception
- NeurIPS 2026On the Complexity of Discounted Robust MDPs with $L_p$ Uncertainty Sets
- NeurIPS 2026On the Origin of Algorithmic Progress in AI: Evidence from Language Model Pre-Training
- NeurIPS 2026One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
- NeurIPS 2026One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
- NeurIPS 2026One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective
- NeurIPS 2026One-Time Soft Alignment Enables Resilient Learning without Weight Transport
- NeurIPS 2026Online Change-point Detection using Foundation Probabilistic Forecasting Models
- NeurIPS 2026Optimal Contextual Pricing under Agnostic Non-Lipschitz Demand
- NeurIPS 2026Ordinary Least Squares as an Attention Mechanism
- NeurIPS 2026PAC-Bayesian Bounds for Learning Partially Observed Stochastic Linear Time-Invariant State-Space Systems with Inputs and Sub-Gaussian Noise
- NeurIPS 2026PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents
- NeurIPS 2026Paloma: Phase-Conditioned Residual Modulation for Time Series Forecasting
- NeurIPS 2026PAMod: Modeling Cyclical Shifts via Phase-Amplitude Modulation for Non-stationary Time Series Forecasting
- NeurIPS 2026PhyTS: A Benchmark for Scientific Time Series
- NeurIPS 2026Polynomial-Time Algorithm for Thiele Voting Rules with Voter Interval Preferences
- NeurIPS 2026Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals
- NeurIPS 2026Position: Robust Reasoning Requires Internal Time, Not Scale Alone
- NeurIPS 2026Precision-Pyramid: Towards real-time neural decoding for fault-tolerant quantum computing
- NeurIPS 2026Predictive Surprise as Self-Grounding Concept Bottleneck for Interpretable Time Series
- NeurIPS 2026Prior as Geometry, Not Generator: Weak-Diffusion Test-Time Reconstruction for Dynamic MRI
- NeurIPS 2026PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation
- NeurIPS 2026Problem-Dependent Dynamic Regret over a Predictor Class with One-Gradient Feedback
- NeurIPS 2026ProCTI: Prototype-Refined Global Conditioning for Diffusion-Based Time Series Imputation
- NeurIPS 2026Progressive Memory Transformer: Memory-Aware Attention for Time-Series
- NeurIPS 2026Prompt–Activation Duality: Improving Activation Steering via Attention-Level Interventions
- NeurIPS 2026Proper Agnostic Learning of Functions of Halfspaces
- NeurIPS 2026Prospective Coding Improves Learning in Deep Continuous-Time Recurrent Networks
- NeurIPS 2026Provable Test-Time Scaling for Beam Search in LLM Reasoning
- NeurIPS 2026ProxySearch: Decoupled Inference-Time Scaling for Diffusion Models via Asymmetric Noise-Rank Transfer
- NeurIPS 2026QWaveNet: Quantum-Enhanced Wavelet Network for Time Series Forecasting
- NeurIPS 2026Raw-Routed Mixture of Adapters: A Causal Intervention for Routing Collapse in Time Series Foundation Models
- NeurIPS 2026Reference-Guided Training: Adaptive Gradient Scaling via Per-Sample Loss Comparisons
- NeurIPS 2026Resolving Time-Frequency Ridge Crossings via Frequency-Rate Lifting
- NeurIPS 2026Response Time Enhances Alignment with Heterogeneous Preferences
- NeurIPS 2026Rethinking Expressivity and Efficiency in Test-Time Training
- NeurIPS 2026Rethinking Post-Training Recipes for Multimodal Time-Series Forecasting
- NeurIPS 2026Rethinking Time Series Tokenization from a Frequency Perspective
- NeurIPS 2026Retrieval Over Training: Similarity search-based Model Selection for Time Series Anomaly Detection
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。