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

75 papers, page 2 of 2

51. NeurIPS 2025Computational Efficiency under Covariate Shift in Kernel Ridge Regression
52. NeurIPS 2025Discovering Symbolic Partial Differential Equation by Abductive Learning
53. NeurIPS 2025Enhancing Deep Batch Active Learning for Regression with Imperfect Data Guided Selection
54. NeurIPS 2025Epistemic Uncertainty Estimation in Regression Ensemble Models with Pairwise Epistemic Estimators
55. NeurIPS 2025FAME: Adaptive Functional Attention with Expert Routing for Function-on-Function Regression
56. NeurIPS 2025FIGRDock: Fast Interaction-Guided Regression for Flexible Docking
57. NeurIPS 2025Generalization vs Specialization under Concept Shift
58. NeurIPS 2025Graph-based Symbolic Regression with Invariance and Constraint Encoding
59. NeurIPS 2025Improving Monte Carlo Tree Search for Symbolic Regression
60. NeurIPS 2025Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination
61. NeurIPS 2025Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression
62. NeurIPS 2025Neural Collapse in Cumulative Link Models for Ordinal Regression: An Analysis with Unconstrained Feature Model
63. NeurIPS 2025Nonparametric Quantile Regression with ReLU-Activated Recurrent Neural Networks
64. NeurIPS 2025Optimal kernel regression bounds under energy-bounded noise
65. NeurIPS 2025Optimal Rates in Continual Linear Regression via Increasing Regularization
66. NeurIPS 2025Personalized Decision Modeling: Utility Optimization or Textualized-Symbolic Reasoning
67. NeurIPS 2025Regularized least squares learning with heavy-tailed noise is minimax optimal
68. NeurIPS 2025Risk Bounds For Distributional Regression
69. NeurIPS 2025Robust Estimation Under Heterogeneous Corruption Rates
70. NeurIPS 2025Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
71. NeurIPS 2025Statistical Inference for Gradient Boosting Regression
72. NeurIPS 2025SymMaP: Improving Computational Efficiency in Linear Solvers through Symbolic Preconditioning
73. NeurIPS 2025Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
74. NeurIPS 2025TranSUN: A Preemptive Paradigm to Eradicate Retransformation Bias Intrinsically from Regression Models in Recommender Systems
75. NeurIPS 2025Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows

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.