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

81 papers, page 1 of 2

1. CVPR 2024Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction
2. CVPR 2024Deep Imbalanced Regression via Hierarchical Classification Adjustment
3. CVPR 2024Deep Single Image Camera Calibration by Heatmap Regression to Recover Fisheye Images Under Manhattan World Assumption
4. CVPR 2024Map-Relative Pose Regression for Visual Re-Localization
5. CVPR 2024Neural Refinement for Absolute Pose Regression with Feature Synthesis
6. CVPR 2024Reg-PTQ: Regression-specialized Post-training Quantization for Fully Quantized Object Detector
7. CVPR 2024Riemannian Multinomial Logistics Regression for SPD Neural Networks
8. CVPR 2024Seg2Reg: Differentiable 2D Segmentation to 1D Regression Rendering for 360 Room Layout Reconstruction
9. CVPR 2024Spatial-Aware Regression for Keypoint Localization
10. CVPR 2024ZeroShape: Regression-based Zero-shot Shape Reconstruction
11. ICLR 2024An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
12. ICLR 2024Conformal Prediction via Regression-as-Classification
13. ICLR 2024Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
14. ICLR 2024Graphical Multioutput Gaussian Process with Attention
15. ICLR 2024How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
16. ICLR 2024LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints
17. ICLR 2024ODEFormer: Symbolic Regression of Dynamical Systems with Transformers
18. ICLR 2024Reinforcement Symbolic Regression Machine
19. ICLR 2024Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework
20. ICLR 2024Risk Bounds of Accelerated SGD for Overparameterized Linear Regression
21. ICLR 2024SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training
22. ICLR 2024Spectrally Transformed Kernel Regression
23. ICLR 2024SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
24. ICLR 2024SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
25. ICLR 2024Transformers can optimally learn regression mixture models
26. ICML 2024$H$-Consistency Guarantees for Regression
27. ICML 2024A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
28. ICML 2024Agnostic Sample Compression Schemes for Regression
29. ICML 2024Beyond the Norms: Detecting Prediction Errors in Regression Models
30. ICML 2024Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
31. ICML 2024Coresets for Multiple $\ell_p$ Regression
32. ICML 2024Deep Regression Representation Learning with Topology
33. ICML 2024Differentially Private Post-Processing for Fair Regression
34. ICML 2024Federated Neuro-Symbolic Learning
35. ICML 2024First-Order Manifold Data Augmentation for Regression Learning
36. ICML 2024Generalization in Kernel Regression Under Realistic Assumptions
37. ICML 2024Geometry-Aware Instrumental Variable Regression
38. ICML 2024Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing
39. ICML 2024Neuro-Symbolic Temporal Point Processes
40. ICML 2024No Double Descent in Principal Component Regression: A High-Dimensional Analysis
41. ICML 2024Online Linear Regression in Dynamic Environments via Discounting
42. ICML 2024Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
43. ICML 2024PAGER: Accurate Failure Characterization in Deep Regression Models
44. ICML 2024Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models
45. ICML 2024Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
46. ICML 2024Simulation-Based Inference with Quantile Regression
47. ICML 2024TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression
48. ICML 2024Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
49. ICML 2024Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression
50. NeurIPS 2024A Comprehensive Analysis on the Learning Curve in Kernel Ridge 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.