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 757 篇，第 4 / 16 页

  1. NeurIPS 2026Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
  2. NeurIPS 2026Neural Fractional Stochastic Differential Equations
  3. NeurIPS 2026Neural Neural Scaling Laws
  4. NeurIPS 2026Neural Optimal Transport in Hilbert Spaces
  5. NeurIPS 2026Neurosymbolic Learning for Inference-Time Argumentation
  6. NeurIPS 2026NOCE-Net: Representation Learning for Battery Operational Context via Nested Sequence Modelling
  7. NeurIPS 2026NPUsper: Eliminating Redundant Computation for Real-Time Whisper on Mobile NPUs
  8. NeurIPS 2026OATS: Online Data Augmentation for Time Series Foundation Models
  9. NeurIPS 2026Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
  10. NeurIPS 2026Observations Drift, Structures Remain: Structural Pretraining with Time Alignment for Electromagnetic Signals
  11. NeurIPS 2026ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow
  12. NeurIPS 2026OHATP: Graph Anomaly Detection with Orthogonal-Hyperspherical Augmentation and Topology Perception
  13. NeurIPS 2026On the Complexity of Discounted Robust MDPs with $L_p$ Uncertainty Sets
  14. NeurIPS 2026On the Origin of Algorithmic Progress in AI: Evidence from Language Model Pre-Training
  15. NeurIPS 2026One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
  16. NeurIPS 2026One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
  17. NeurIPS 2026One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective
  18. NeurIPS 2026One-Time Soft Alignment Enables Resilient Learning without Weight Transport
  19. NeurIPS 2026Online Change-point Detection using Foundation Probabilistic Forecasting Models
  20. NeurIPS 2026Optimal Contextual Pricing under Agnostic Non-Lipschitz Demand
  21. NeurIPS 2026Ordinary Least Squares as an Attention Mechanism
  22. NeurIPS 2026PAC-Bayesian Bounds for Learning Partially Observed Stochastic Linear Time-Invariant State-Space Systems with Inputs and Sub-Gaussian Noise
  23. NeurIPS 2026PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents
  24. NeurIPS 2026Paloma: Phase-Conditioned Residual Modulation for Time Series Forecasting
  25. NeurIPS 2026PAMod: Modeling Cyclical Shifts via Phase-Amplitude Modulation for Non-stationary Time Series Forecasting
  26. NeurIPS 2026PhyTS: A Benchmark for Scientific Time Series
  27. NeurIPS 2026Polynomial-Time Algorithm for Thiele Voting Rules with Voter Interval Preferences
  28. NeurIPS 2026Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals
  29. NeurIPS 2026Position: Robust Reasoning Requires Internal Time, Not Scale Alone
  30. NeurIPS 2026Precision-Pyramid: Towards real-time neural decoding for fault-tolerant quantum computing
  31. NeurIPS 2026Predictive Surprise as Self-Grounding Concept Bottleneck for Interpretable Time Series
  32. NeurIPS 2026Prior as Geometry, Not Generator: Weak-Diffusion Test-Time Reconstruction for Dynamic MRI
  33. NeurIPS 2026PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation
  34. NeurIPS 2026Problem-Dependent Dynamic Regret over a Predictor Class with One-Gradient Feedback
  35. NeurIPS 2026ProCTI: Prototype-Refined Global Conditioning for Diffusion-Based Time Series Imputation
  36. NeurIPS 2026Progressive Memory Transformer: Memory-Aware Attention for Time-Series
  37. NeurIPS 2026Prompt–Activation Duality: Improving Activation Steering via Attention-Level Interventions
  38. NeurIPS 2026Proper Agnostic Learning of Functions of Halfspaces
  39. NeurIPS 2026Prospective Coding Improves Learning in Deep Continuous-Time Recurrent Networks
  40. NeurIPS 2026Provable Test-Time Scaling for Beam Search in LLM Reasoning
  41. NeurIPS 2026ProxySearch: Decoupled Inference-Time Scaling for Diffusion Models via Asymmetric Noise-Rank Transfer
  42. NeurIPS 2026QWaveNet: Quantum-Enhanced Wavelet Network for Time Series Forecasting
  43. NeurIPS 2026Raw-Routed Mixture of Adapters: A Causal Intervention for Routing Collapse in Time Series Foundation Models
  44. NeurIPS 2026Reference-Guided Training: Adaptive Gradient Scaling via Per-Sample Loss Comparisons
  45. NeurIPS 2026Resolving Time-Frequency Ridge Crossings via Frequency-Rate Lifting
  46. NeurIPS 2026Response Time Enhances Alignment with Heterogeneous Preferences
  47. NeurIPS 2026Rethinking Expressivity and Efficiency in Test-Time Training
  48. NeurIPS 2026Rethinking Post-Training Recipes for Multimodal Time-Series Forecasting
  49. NeurIPS 2026Rethinking Time Series Tokenization from a Frequency Perspective
  50. 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"}

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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