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 298 篇，第 5 / 6 页

  1. NeurIPS 2026RnR: a meta-solver for causal discovery in undersampled time series data
  2. NeurIPS 2026Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization
  3. NeurIPS 2026Robust Residual Correction via Selective Deployment for Time Series Forecasting
  4. NeurIPS 2026Robust Stream Classification using Time Neutralising Decision Trees
  5. NeurIPS 2026Rubato: Signature Attention for Irregular Multivariate Time Series Forecasting
  6. NeurIPS 2026Runtime Analysis of Cartesian Genetic Programming on MAX: A Proven Exponential Speedup
  7. NeurIPS 2026S3Former: Sequential, Structural, and Statistical Fusion for Continuous-Time Dynamic Graphs
  8. NeurIPS 2026Safe Active Learning with Future Viability Guarantees in Time-Series Models
  9. NeurIPS 2026SDFlow: Similarity-Driven Flow Matching for Time Series Generation
  10. NeurIPS 2026SDHilb: Schrödinger Dynamics-Guided Neural Network with Adaptive Multi-Scale Hilbert Transform for Time Series Forecasting
  11. NeurIPS 2026Self-Trained Verification for Training- and Test-Time Self-Improvement
  12. NeurIPS 2026Semantically Complementary Spectral Views Learning for Graph-Level Anomaly Detection
  13. NeurIPS 2026SetAD: Semi-Supervised Anomaly Learning in Contextual Sets
  14. NeurIPS 2026SIGMA: A Sigmoid-Gated Sampler for Test-Time Scaling in Diffusion Language Models
  15. NeurIPS 2026SLiDE: Structured Linear Dynamics for Forecasting with Exogenous Inputs
  16. NeurIPS 2026SPECS: Faster Test-Time Scaling through Speculative Drafts and Dynamic Switching
  17. NeurIPS 2026Spectral Energy Allocation Enables Source-Free Domain Adaptation in Time Series Forecasting
  18. NeurIPS 2026Spectral Transformer Neural Processes
  19. NeurIPS 2026Spikes as Detectors: Phase-Conditioned Spiking Dynamics for Time-Series Anomaly Detection
  20. NeurIPS 2026SpikeSTAG: A Dendritic Compartmental Spiking Graph Network for Multivariate Time-Series Forecasting
  21. NeurIPS 2026Stability-Weighted Direction Regularization Disentangles Generator Shortcuts from Detection Signal
  22. NeurIPS 2026Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping
  23. NeurIPS 2026Stable Alpha: Adversarial Invariant Representation Learning for Nonlinear Asset Pricing under Temporal Distribution Shifts
  24. NeurIPS 2026Stable Resolution-Invariant Emulation in Entropically Controlled Kinetic Methods
  25. NeurIPS 2026STAR: Boosting Time Series Foundation Models for Anomaly Detection Through State-Aware Adapter
  26. NeurIPS 2026SteerCast: Retrieval-Based Latent Steering for Decoder-Only Time Series Forecasting
  27. NeurIPS 2026STEP: Learning STructured Embeddings for Progressive Time Series
  28. NeurIPS 2026Stochastic Approximation Approach for Decentralized Optimization on Time Varying Random Networks
  29. NeurIPS 2026Strongly Adaptive Online Learning with Time-Varying Movement Cost
  30. NeurIPS 2026Supervision Recovery for Time Series Anomaly Detection via Counterfactual Pairing
  31. NeurIPS 2026TailFix: Mitigating Error Accumulation and Correcting Tail Deterioration in Long-Horizon Forecasting
  32. NeurIPS 2026TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
  33. NeurIPS 2026Temporal Island Sparse Autoencoders for Interpreting Clinical Time-Series Models
  34. NeurIPS 2026Temporal-Scale Sensitivity in Time-Series Tokenization and Scale-Robust Token Estimation by Gated Sum
  35. NeurIPS 2026TENET: Time-point Encoding Network for Multivariate Time Series Anomaly Detection
  36. NeurIPS 2026Test Time Search Requires Training for Diversity
  37. NeurIPS 2026Test time training enhances in-context learning of nonlinear functions
  38. NeurIPS 2026Test-Time Adaptation via Self-Reinforced Optimal Transport for Zero-Shot OOD Detection with Vision–Language Models
  39. NeurIPS 2026Test-Time Compute Games
  40. NeurIPS 2026Test-Time Conditioning with Representation-Aligned Visual Features
  41. NeurIPS 2026Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles
  42. NeurIPS 2026Test-Time Graph Anomaly Detection via Shifted Augmentation with Dynamic Objective Scheduling
  43. NeurIPS 2026Test-Time Learning with an Evolving Library
  44. NeurIPS 2026Test-Time Prompt-Agnostic Decomposition
  45. NeurIPS 2026Test-time Risk Adaptation with Mixture of Agents
  46. NeurIPS 2026Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck
  47. NeurIPS 2026Test-time Scaling of Diffusions with Flow Maps
  48. NeurIPS 2026Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
  49. NeurIPS 2026Test-Time Sequential Steering of Diffusion Models via Preconditioned Crank-Nicolson
  50. NeurIPS 2026The BV4 Benchmark for Unsupervised Anomaly Detection in High-Dimensional Spectral Data Streams

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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