Symbolic Regression papers, 2023–2026

Key findings

• Symbolic Regression went from 63 papers in 2023 to 97 in 2026, roughly 1.5x in three years.
• NeurIPS publishes the most Symbolic Regression work: 118 papers from 2023 to 2026, 37% of the four-venue total.
• The fastest-growing overlap is with Theory · learning theory: papers tagged with both rose from 1 in 2023 to 10 in 2026.
• Among the 5 topics under Program Synthesis, it ranks #1 by 2026 paper count; the fastest grower in the group, Theorem Proving, is up 13x versus 1.5x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Symbolic Regression papers

316 papers, page 4 of 7

151. NeurIPS 2025Epistemic Uncertainty Estimation in Regression Ensemble Models with Pairwise Epistemic Estimators
152. NeurIPS 2025FAME: Adaptive Functional Attention with Expert Routing for Function-on-Function Regression
153. NeurIPS 2025FIGRDock: Fast Interaction-Guided Regression for Flexible Docking
154. NeurIPS 2025Generalization vs Specialization under Concept Shift
155. NeurIPS 2025Graph-based Symbolic Regression with Invariance and Constraint Encoding
156. NeurIPS 2025Improving Monte Carlo Tree Search for Symbolic Regression
157. NeurIPS 2025Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination
158. NeurIPS 2025Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression
159. NeurIPS 2025Neural Collapse in Cumulative Link Models for Ordinal Regression: An Analysis with Unconstrained Feature Model
160. NeurIPS 2025Nonparametric Quantile Regression with ReLU-Activated Recurrent Neural Networks
161. NeurIPS 2025Optimal kernel regression bounds under energy-bounded noise
162. NeurIPS 2025Optimal Rates in Continual Linear Regression via Increasing Regularization
163. NeurIPS 2025Personalized Decision Modeling: Utility Optimization or Textualized-Symbolic Reasoning
164. NeurIPS 2025Regularized least squares learning with heavy-tailed noise is minimax optimal
165. NeurIPS 2025Risk Bounds For Distributional Regression
166. NeurIPS 2025Robust Estimation Under Heterogeneous Corruption Rates
167. NeurIPS 2025Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
168. NeurIPS 2025Statistical Inference for Gradient Boosting Regression
169. NeurIPS 2025SymMaP: Improving Computational Efficiency in Linear Solvers through Symbolic Preconditioning
170. NeurIPS 2025Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
171. NeurIPS 2025TranSUN: A Preemptive Paradigm to Eradicate Retransformation Bias Intrinsically from Regression Models in Recommender Systems
172. NeurIPS 2025Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows
173. CVPR 2024Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction
174. CVPR 2024Deep Imbalanced Regression via Hierarchical Classification Adjustment
175. CVPR 2024Deep Single Image Camera Calibration by Heatmap Regression to Recover Fisheye Images Under Manhattan World Assumption
176. CVPR 2024Map-Relative Pose Regression for Visual Re-Localization
177. CVPR 2024Neural Refinement for Absolute Pose Regression with Feature Synthesis
178. CVPR 2024Reg-PTQ: Regression-specialized Post-training Quantization for Fully Quantized Object Detector
179. CVPR 2024Riemannian Multinomial Logistics Regression for SPD Neural Networks
180. CVPR 2024Seg2Reg: Differentiable 2D Segmentation to 1D Regression Rendering for 360 Room Layout Reconstruction
181. CVPR 2024Spatial-Aware Regression for Keypoint Localization
182. CVPR 2024ZeroShape: Regression-based Zero-shot Shape Reconstruction
183. ICLR 2024An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
184. ICLR 2024Conformal Prediction via Regression-as-Classification
185. ICLR 2024Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
186. ICLR 2024Graphical Multioutput Gaussian Process with Attention
187. ICLR 2024How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
188. ICLR 2024LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints
189. ICLR 2024ODEFormer: Symbolic Regression of Dynamical Systems with Transformers
190. ICLR 2024Reinforcement Symbolic Regression Machine
191. ICLR 2024Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework
192. ICLR 2024Risk Bounds of Accelerated SGD for Overparameterized Linear Regression
193. ICLR 2024SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training
194. ICLR 2024Spectrally Transformed Kernel Regression
195. ICLR 2024SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
196. ICLR 2024SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
197. ICLR 2024Transformers can optimally learn regression mixture models
198. ICML 2024$H$-Consistency Guarantees for Regression
199. ICML 2024A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
200. ICML 2024Agnostic Sample Compression Schemes for Regression

FAQ

How many Symbolic Regression papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

316 in total: 63 in 2023, 81 in 2024, 75 in 2025, 97 in 2026.

How many Symbolic Regression papers are at NeurIPS 2026?

NeurIPS 2026 has 34 Symbolic Regression papers, versus 30 the year before.

How many Symbolic Regression papers are at ICLR 2026?

ICLR 2026 has 24 Symbolic Regression papers, versus 22 the year before.

How many Symbolic Regression papers are at ICML 2026?

ICML 2026 has 36 Symbolic Regression papers, versus 21 the year before.

How many Symbolic Regression papers are at CVPR 2026?

CVPR 2026 has 3 Symbolic Regression papers, versus 2 the year before.

Which conference publishes the most Symbolic Regression papers?

NeurIPS, with 118 papers from 2023 to 2026.