符号回归论文趋势 2023–2026

主要结论

• 符号回归论文从 2023 年的 63 篇增长到 2026 年的 97 篇，三年间扩大到约 1.5 倍。
• NeurIPS 是发符号回归论文最多的会议，2023–2026 年共 118 篇，占四个会议总量的 37%。
• 交叉方向里涨得最快的是理论 · learning theory：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 10 篇。
• 在「程序综合」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的定理证明是 13 倍，符号回归是 1.5 倍。

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 2026Conformal Prediction for Distribution-to-Distribution Regression
• ICML 2026Approximation Bounds for Transformer Networks with Application to Regression
• ICLR 2026Fast Estimation of Wasserstein Distances via Regression on Sliced Wasserstein Distances
• CVPR 2026CoLoR The Devil is in Scene Coordinate Regression for Large-Scale
• NeurIPS 2025Ascent Fails to Forget
• ICML 2025Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression
• ICLR 2025A Graph Enhanced Symbolic Discovery Framework For Efficient Logic Optimization
• CVPR 2025R-SCoRe: Revisiting Scene Coordinate Regression for Robust Large-Scale Visual Localization
• NeurIPS 2024Distributed Sparse Regression via Penalization
• ICML 2024$H$-Consistency Guarantees for Regression
• ICLR 2024Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
• CVPR 2024Map-Relative Pose Regression for Visual Re-Localization
• NeurIPS 2023Collaboratively Learning Linear Models with Structured Missing Data
• ICML 2023A Nearly-Optimal Bound for Fast Regression with $\ell_\infty$ Guarantee
• ICLR 2023Fast Nonlinear Vector Quantile Regression
• CVPR 2023DistilPose: Tokenized Pose Regression With Heatmap Distillation
• NeurIPS 2026DASS: A Solver-Agnostic Dynamic Auxiliary Search Strategy for Symbolic Regression
• ICML 2026AutoNumerics-Zero: Automated Discovery of State-of-the-Art Mathematical Functions
• ICLR 2026GenSR: Symbolic regression based on equation generative space
• CVPR 2026Sparse-View Localization via Online Neural 3D Regression

全部符号回归论文

共 63 篇，第 1 / 2 页

1. CVPR 2023DistilPose: Tokenized Pose Regression With Heatmap Distillation
2. CVPR 2023HypLiLoc: Towards Effective LiDAR Pose Regression With Hyperbolic Fusion
3. CVPR 2023TRACE: 5D Temporal Regression of Avatars With Dynamic Cameras in 3D Environments
4. ICLR 2023Binding Language Models in Symbolic Languages
5. ICLR 2023Deep Generative Symbolic Regression
6. ICLR 2023Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?
7. ICLR 2023Easy Differentially Private Linear Regression
8. ICLR 2023Fast Nonlinear Vector Quantile Regression
9. ICLR 2023Improving Deep Regression with Ordinal Entropy
10. ICLR 2023Learning Label Encodings for Deep Regression
11. ICLR 2023Learning Symbolic Models for Graph-structured Physical Mechanism
12. ICLR 2023Neuro-Symbolic Procedural Planning with Commonsense Prompting
13. ICLR 2023On the Saturation Effect of Kernel Ridge Regression
14. ICLR 2023Optimal Activation Functions for the Random Features Regression Model
15. ICLR 2023Provably Auditing Ordinary Least Squares in Low Dimensions
16. ICLR 2023Rethinking Symbolic Regression: Morphology and Adaptability in the Context of Evolutionary Algorithms
17. ICLR 2023Softened Symbol Grounding for Neuro-symbolic Systems
18. ICLR 2023Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search
19. ICLR 2023Transformer-based model for symbolic regression via joint supervised learning
20. ICLR 2023Weighted Clock Logic Point Process
21. ICML 2023A Nearly-Optimal Bound for Fast Regression with $\ell_\infty$ Guarantee
22. ICML 2023Controllable Neural Symbolic Regression
23. ICML 2023Data-Driven Subgroup Identification for Linear Regression
24. ICML 2023Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
25. ICML 2023Deep Regression Unlearning
26. ICML 2023Differentially Private Distributed Bayesian Linear Regression with MCMC
27. ICML 2023Efficient List-Decodable Regression using Batches
28. ICML 2023Extrapolated Random Tree for Regression
29. ICML 2023Flexible Model Aggregation for Quantile Regression
30. ICML 2023Gradient Descent Converges Linearly for Logistic Regression on Separable Data
31. ICML 2023Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression
32. ICML 2023Kernel Logistic Regression Approximation of an Understandable ReLU Neural Network
33. ICML 2023Multicalibration as Boosting for Regression
34. ICML 2023Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel Regression
35. ICML 2023On the Optimality of Misspecified Kernel Ridge Regression
36. ICML 2023Optimizing Hyperparameters with Conformal Quantile Regression
37. ICML 2023Regression with Label Permutation in Generalized Linear Model
38. ICML 2023Regression with Sensor Data Containing Incomplete Observations
39. ICML 2023Second-order regression models exhibit progressive sharpening to the edge of stability
40. ICML 2023Sketched Ridgeless Linear Regression: The Role of Downsampling
41. ICML 2023Weakly Supervised Regression with Interval Targets
42. NeurIPS 2023Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression
43. NeurIPS 2023Collaboratively Learning Linear Models with Structured Missing Data
44. NeurIPS 2023D-CIPHER: Discovery of Closed-form Partial Differential Equations
45. NeurIPS 2023Demographic Parity Constrained Minimax Optimal Regression under Linear Model
46. NeurIPS 2023Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods
47. NeurIPS 2023Efficient Symbolic Policy Learning with Differentiable Symbolic Expression
48. NeurIPS 2023Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation
49. NeurIPS 2023MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition
50. NeurIPS 2023Network Regression with Graph Laplacians

常见问题

2023–2026 年四大会议一共有多少篇符号回归论文？

共 316 篇，按年份分别是 2023 年 63 篇、2024 年 81 篇、2025 年 75 篇、2026 年 97 篇。

NeurIPS 2026 有多少篇符号回归论文？

NeurIPS 2026 有 34 篇符号回归论文，上一届是 30 篇。

ICLR 2026 有多少篇符号回归论文？

ICLR 2026 有 24 篇符号回归论文，上一届是 22 篇。

ICML 2026 有多少篇符号回归论文？

ICML 2026 有 36 篇符号回归论文，上一届是 21 篇。

CVPR 2026 有多少篇符号回归论文？

CVPR 2026 有 3 篇符号回归论文，上一届是 2 篇。

哪个会议的符号回归论文最多？

NeurIPS，2023–2026 年共 118 篇。