Symbolic Regression papers, 2023–2026
Equation discovery
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 316 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 22 | 17 | 21 | 3 | 63 |
| 2024 | 32 | 15 | 24 | 10 | 81 |
| 2025 | 30 | 22 | 21 | 2 | 75 |
| 2026 | 34 | 24 | 36 | 3 | 97 |
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 6 of 7
- NeurIPS 2024The Space Complexity of Approximating Logistic Loss
- NeurIPS 2024Towards the Dynamics of a DNN Learning Symbolic Interactions
- NeurIPS 2024Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression
- CVPR 2023DistilPose: Tokenized Pose Regression With Heatmap Distillation
- CVPR 2023HypLiLoc: Towards Effective LiDAR Pose Regression With Hyperbolic Fusion
- CVPR 2023TRACE: 5D Temporal Regression of Avatars With Dynamic Cameras in 3D Environments
- ICLR 2023Binding Language Models in Symbolic Languages
- ICLR 2023Deep Generative Symbolic Regression
- ICLR 2023Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?
- ICLR 2023Easy Differentially Private Linear Regression
- ICLR 2023Fast Nonlinear Vector Quantile Regression
- ICLR 2023Improving Deep Regression with Ordinal Entropy
- ICLR 2023Learning Label Encodings for Deep Regression
- ICLR 2023Learning Symbolic Models for Graph-structured Physical Mechanism
- ICLR 2023Neuro-Symbolic Procedural Planning with Commonsense Prompting
- ICLR 2023On the Saturation Effect of Kernel Ridge Regression
- ICLR 2023Optimal Activation Functions for the Random Features Regression Model
- ICLR 2023Provably Auditing Ordinary Least Squares in Low Dimensions
- ICLR 2023Rethinking Symbolic Regression: Morphology and Adaptability in the Context of Evolutionary Algorithms
- ICLR 2023Softened Symbol Grounding for Neuro-symbolic Systems
- ICLR 2023Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search
- ICLR 2023Transformer-based model for symbolic regression via joint supervised learning
- ICLR 2023Weighted Clock Logic Point Process
- ICML 2023A Nearly-Optimal Bound for Fast Regression with $\ell_\infty$ Guarantee
- ICML 2023Controllable Neural Symbolic Regression
- ICML 2023Data-Driven Subgroup Identification for Linear Regression
- ICML 2023Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
- ICML 2023Deep Regression Unlearning
- ICML 2023Differentially Private Distributed Bayesian Linear Regression with MCMC
- ICML 2023Efficient List-Decodable Regression using Batches
- ICML 2023Extrapolated Random Tree for Regression
- ICML 2023Flexible Model Aggregation for Quantile Regression
- ICML 2023Gradient Descent Converges Linearly for Logistic Regression on Separable Data
- ICML 2023Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression
- ICML 2023Kernel Logistic Regression Approximation of an Understandable ReLU Neural Network
- ICML 2023Multicalibration as Boosting for Regression
- ICML 2023Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel Regression
- ICML 2023On the Optimality of Misspecified Kernel Ridge Regression
- ICML 2023Optimizing Hyperparameters with Conformal Quantile Regression
- ICML 2023Regression with Label Permutation in Generalized Linear Model
- ICML 2023Regression with Sensor Data Containing Incomplete Observations
- ICML 2023Second-order regression models exhibit progressive sharpening to the edge of stability
- ICML 2023Sketched Ridgeless Linear Regression: The Role of Downsampling
- ICML 2023Weakly Supervised Regression with Interval Targets
- NeurIPS 2023Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression
- NeurIPS 2023Collaboratively Learning Linear Models with Structured Missing Data
- NeurIPS 2023D-CIPHER: Discovery of Closed-form Partial Differential Equations
- NeurIPS 2023Demographic Parity Constrained Minimax Optimal Regression under Linear Model
- NeurIPS 2023Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods
- NeurIPS 2023Efficient Symbolic Policy Learning with Differentiable Symbolic Expression
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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.