驾驶仿真论文趋势 2023–2026

闭环仿真

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 5,882 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

驾驶仿真论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023219182218350969
20244101763583641,308
20255422282753601,405
20269403133635842,200

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

全部驾驶仿真论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 969 篇，第 13 / 20 页

  1. ICML 2023GC-Flow: A Graph-Based Flow Network for Effective Clustering
  2. ICML 2023GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
  3. ICML 2023Generalization Analysis for Contrastive Representation Learning
  4. ICML 2023Generalized Teacher Forcing for Learning Chaotic Dynamics
  5. ICML 2023Generating Language Corrections for Teaching Physical Control Tasks
  6. ICML 2023GFlowNet-EM for Learning Compositional Latent Variable Models
  7. ICML 2023GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration
  8. ICML 2023Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models
  9. ICML 2023Global optimality for Euclidean CCCP under Riemannian convexity
  10. ICML 2023GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming
  11. ICML 2023Gradient Descent Converges Linearly for Logistic Regression on Separable Data
  12. ICML 2023Gradient-based Wang--Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space
  13. ICML 2023Group Equivariant Fourier Neural Operators for Partial Differential Equations
  14. ICML 2023H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features
  15. ICML 2023Half-Hop: A graph upsampling approach for slowing down message passing
  16. ICML 2023Hiding Data Helps: On the Benefits of Masking for Sparse Coding
  17. ICML 2023High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors
  18. ICML 2023How Jellyfish Characterise Alternating Group Equivariant Neural Networks
  19. ICML 2023How Powerful are Shallow Neural Networks with Bandlimited Random Weights?
  20. ICML 2023How to address monotonicity for model risk management?
  21. ICML 2023Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
  22. ICML 2023Identifying Useful Learnwares for Heterogeneous Label Spaces
  23. ICML 2023Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression
  24. ICML 2023Improved Algorithms for Multi-period Multi-class Packing Problems with Bandit Feedback
  25. ICML 2023Improved Algorithms for White-Box Adversarial Streams
  26. ICML 2023Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation
  27. ICML 2023Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
  28. ICML 2023Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models
  29. ICML 2023Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics
  30. ICML 2023Interval Bound Interpolation for Few-shot Learning with Few Tasks
  31. ICML 2023Is Learning Summary Statistics Necessary for Likelihood-free Inference?
  32. ICML 2023Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation
  33. ICML 2023Learning Affinity with Hyperbolic Representation for Spatial Propagation
  34. ICML 2023Learning Deep Time-index Models for Time Series Forecasting
  35. ICML 2023Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data
  36. ICML 2023Locally Regularized Neural Differential Equations: Some Black Boxes were meant to remain closed!
  37. ICML 2023LookupFFN: Making Transformers Compute-lite for CPU inference
  38. ICML 2023Looped Transformers as Programmable Computers
  39. ICML 2023Loss Balancing for Fair Supervised Learning
  40. ICML 2023Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set
  41. ICML 2023LSDS++ : Dual Sampling for Accelerated k-means++
  42. ICML 2023Memory-Based Dual Gaussian Processes for Sequential Learning
  43. ICML 2023Mixing Predictions for Online Metric Algorithms
  44. ICML 2023Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning
  45. ICML 2023ModelDiff: A Framework for Comparing Learning Algorithms
  46. ICML 2023Monotonic Location Attention for Length Generalization
  47. ICML 2023MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks
  48. ICML 2023Multicalibration as Boosting for Regression
  49. ICML 2023Multiple Thinking Achieving Meta-Ability Decoupling for Object Navigation
  50. ICML 2023Multiplier Bootstrap-based Exploration

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 查驾驶仿真在 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": "simulation-for-driving"}

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常见问题

2023–2026 年四大会议一共有多少篇驾驶仿真论文？
共 5,882 篇，按年份分别是 2023 年 969 篇、2024 年 1,308 篇、2025 年 1,405 篇、2026 年 2,200 篇。
NeurIPS 2026 有多少篇驾驶仿真论文？
NeurIPS 2026 有 940 篇驾驶仿真论文，上一届是 542 篇。
ICLR 2026 有多少篇驾驶仿真论文？
ICLR 2026 有 313 篇驾驶仿真论文，上一届是 228 篇。
ICML 2026 有多少篇驾驶仿真论文？
ICML 2026 有 363 篇驾驶仿真论文，上一届是 275 篇。
CVPR 2026 有多少篇驾驶仿真论文？
CVPR 2026 有 584 篇驾驶仿真论文，上一届是 360 篇。
哪个会议的驾驶仿真论文最多？
NeurIPS，2023–2026 年共 2,111 篇。

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