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

每年论文数

各会议论文数

按年份和会议统计

时间序列论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202391606259272
20241479511468424
202522113115974585
202629822026494876

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

全部时间序列论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 2,156 篇，第 15 / 44 页

  1. NeurIPS 2026Joint Consistency: A Unified Test-Time Aggregation Framework via Energy Minimization
  2. NeurIPS 2026Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
  3. NeurIPS 2026Koopman Generative Operators for Efficient Probabilistic Time-Series Forecasting
  4. NeurIPS 2026Layer Precision Reduction for Deep Anomaly Detection
  5. NeurIPS 2026Learned Lagrangian Models of PDEs via Euler–Lagrange Residual Minimization
  6. NeurIPS 2026Learning Collision‑Free Dispatch Policies for Route‑Wise Decision‑Dependent Anomaly Detection
  7. NeurIPS 2026Learning Planning Budgets in Real-Time RL
  8. NeurIPS 2026Learning to Trigger: Reinforcement Learning at the Large Hadron Collider
  9. NeurIPS 2026Linear-time rule mining under formal guarantees
  10. NeurIPS 2026Lipschitz Dueling Bandits over Continuous Action Spaces
  11. NeurIPS 2026LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling
  12. NeurIPS 2026LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models
  13. NeurIPS 2026Mamba Can Learn Low-Dimensional Targets In-Context via Test-Time Feature Learning
  14. NeurIPS 2026Mamba Flow Matching Neural Processes: Linear-Time Inference for Irregularly Observed Spatial Fields
  15. NeurIPS 2026Marrying Optimal Transport and ODEs for Unified Continuous-Time 4D Reconstruction and Tracking
  16. NeurIPS 2026MDK-MoE: Multi-view Decomposed Kalman Mixture of Experts Framework for Non-stationary Time Series Forecasting
  17. NeurIPS 2026Measure Less, Know More: Self-Supervised Test-Time Feature Acquisition
  18. NeurIPS 2026Measuring Robustness and Efficiency in a Connectome-Constrained Fly Visual System Model on a Collision-Detection Task
  19. NeurIPS 2026Membrane Sensitivity and Deployment Fragility of Learnable Time Constants in Spiking Neural Networks
  20. NeurIPS 2026MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series
  21. NeurIPS 2026MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision
  22. NeurIPS 2026Monotone Inclusion Approach to Weakly Monotone Discrete-Time Finite-Horizon Mean-Field Games
  23. NeurIPS 2026MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series
  24. NeurIPS 2026MSAR: Next-Scale Autoregressive Forecasting for Time Series via Modular Multi-Scale Decoupling
  25. NeurIPS 2026Multivariate Time Series Forecasting needs Cross Variable Loss
  26. NeurIPS 2026Near-Linear Time Generalized Sinkhorn Algorithms for Bounded Genus Graphs
  27. NeurIPS 2026Near-Optimal Regret in Adversarial Kernel Bandits
  28. NeurIPS 2026Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
  29. NeurIPS 2026Neural Fractional Stochastic Differential Equations
  30. NeurIPS 2026Neural Neural Scaling Laws
  31. NeurIPS 2026Neural Optimal Transport in Hilbert Spaces
  32. NeurIPS 2026Neurosymbolic Learning for Inference-Time Argumentation
  33. NeurIPS 2026NOCE-Net: Representation Learning for Battery Operational Context via Nested Sequence Modelling
  34. NeurIPS 2026NPUsper: Eliminating Redundant Computation for Real-Time Whisper on Mobile NPUs
  35. NeurIPS 2026OATS: Online Data Augmentation for Time Series Foundation Models
  36. NeurIPS 2026Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
  37. NeurIPS 2026Observations Drift, Structures Remain: Structural Pretraining with Time Alignment for Electromagnetic Signals
  38. NeurIPS 2026ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow
  39. NeurIPS 2026OHATP: Graph Anomaly Detection with Orthogonal-Hyperspherical Augmentation and Topology Perception
  40. NeurIPS 2026On the Complexity of Discounted Robust MDPs with $L_p$ Uncertainty Sets
  41. NeurIPS 2026On the Origin of Algorithmic Progress in AI: Evidence from Language Model Pre-Training
  42. NeurIPS 2026One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
  43. NeurIPS 2026One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
  44. NeurIPS 2026One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective
  45. NeurIPS 2026One-Time Soft Alignment Enables Resilient Learning without Weight Transport
  46. NeurIPS 2026Online Change-point Detection using Foundation Probabilistic Forecasting Models
  47. NeurIPS 2026Optimal Contextual Pricing under Agnostic Non-Lipschitz Demand
  48. NeurIPS 2026Ordinary Least Squares as an Attention Mechanism
  49. NeurIPS 2026PAC-Bayesian Bounds for Learning Partially Observed Stochastic Linear Time-Invariant State-Space Systems with Inputs and Sub-Gaussian Noise
  50. NeurIPS 2026PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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