符号回归论文趋势 2023–2026
方程发现
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 316 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 22 | 17 | 21 | 3 | 63 |
| 2024 | 32 | 15 | 24 | 10 | 81 |
| 2025 | 30 | 22 | 21 | 2 | 75 |
| 2026 | 34 | 24 | 36 | 3 | 97 |
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 316 篇，第 5 / 7 页
- ICML 2024Beyond the Norms: Detecting Prediction Errors in Regression Models
- ICML 2024Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
- ICML 2024Coresets for Multiple $\ell_p$ Regression
- ICML 2024Deep Regression Representation Learning with Topology
- ICML 2024Differentially Private Post-Processing for Fair Regression
- ICML 2024Federated Neuro-Symbolic Learning
- ICML 2024First-Order Manifold Data Augmentation for Regression Learning
- ICML 2024Generalization in Kernel Regression Under Realistic Assumptions
- ICML 2024Geometry-Aware Instrumental Variable Regression
- ICML 2024Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing
- ICML 2024Neuro-Symbolic Temporal Point Processes
- ICML 2024No Double Descent in Principal Component Regression: A High-Dimensional Analysis
- ICML 2024Online Linear Regression in Dynamic Environments via Discounting
- ICML 2024Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
- ICML 2024PAGER: Accurate Failure Characterization in Deep Regression Models
- ICML 2024Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models
- ICML 2024Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
- ICML 2024Simulation-Based Inference with Quantile Regression
- ICML 2024TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression
- ICML 2024Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
- ICML 2024Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression
- NeurIPS 2024A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression
- NeurIPS 2024A Walsh Hadamard Derived Linear Vector Symbolic Architecture
- NeurIPS 2024Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient
- NeurIPS 2024Attention boosted Individualized Regression
- NeurIPS 2024Continuous Heatmap Regression for Pose Estimation via Implicit Neural Representation
- NeurIPS 2024Data subsampling for Poisson regression with pth-root-link
- NeurIPS 2024Distributed Sparse Regression via Penalization
- NeurIPS 2024Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
- NeurIPS 2024GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules
- NeurIPS 2024High-dimensional (Group) Adversarial Training in Linear Regression
- NeurIPS 2024Implicit Regularization of Decentralized Gradient Descent for Sparse Regression
- NeurIPS 2024Implicit Regularization Paths of Weighted Neural Representations
- NeurIPS 2024Improving Adaptivity via Over-Parameterization in Sequence Models
- NeurIPS 2024Least Squares Regression Can Exhibit Under-Parameterized Double Descent
- NeurIPS 2024Linear Regression using Heterogeneous Data Batches
- NeurIPS 2024Model Collapse Demystified: The Case of Regression
- NeurIPS 2024Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
- NeurIPS 2024Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
- NeurIPS 2024Nonparametric Regression for 3D Point Cloud Learning
- NeurIPS 2024Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
- NeurIPS 2024Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
- NeurIPS 2024Regression under demographic parity constraints via unlabeled post-processing
- NeurIPS 2024Revisiting Differentially Private ReLU Regression
- NeurIPS 2024Robust Sparse Regression with Non-Isotropic Designs
- NeurIPS 2024Sample Selection via Contrastive Fragmentation for Noisy Label Regression
- NeurIPS 2024Symbolic Regression with a Learned Concept Library
- NeurIPS 2024Symmetry-Informed Governing Equation Discovery
- NeurIPS 2024The Prevalence of Neural Collapse in Neural Multivariate Regression
- NeurIPS 2024The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems
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 查符号回归在 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": "symbolic-regression"}
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。