Scaling Up Unbiased Search-based Symbolic Regression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kahlmeyer, Paul, Giesen, Joachim, Habeck, Michael, Voigt, Henrik
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Analyzing Generalization in Pre-Trained Symbolic Regression
by: Voigt, Henrik, et al.
Published: (2025)

Dimension Reduction for Symbolic Regression
by: Kahlmeyer, Paul, et al.
Published: (2025)

Discovering Symmetries of ODEs by Symbolic Regression
by: Kahlmeyer, Paul, et al.
Published: (2025)

Beyond the Training Distribution: Mapping Generalization Boundaries in Neural Program Synthesis
by: Voigt, Henrik, et al.
Published: (2026)

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements
by: Möbius, Julian L., et al.
Published: (2024)

Towards Scaling Laws for Symbolic Regression
by: Otte, David, et al.
Published: (2025)

Improving Monte Carlo Tree Search for Symbolic Regression
by: Huang, Zhengyao, et al.
Published: (2025)

SPINEX_ Symbolic Regression: Similarity-based Symbolic Regression with Explainable Neighbors Exploration
by: Naser, MZ, et al.
Published: (2024)

Neural Structure Embedding for Symbolic Regression via Continuous Structure Search and Coefficient Optimization
by: Memar, Fateme, et al.
Published: (2026)

Diffusion-Based Symbolic Regression
by: Bastiani, Zachary, et al.
Published: (2025)

Decomposable Neuro Symbolic Regression
by: Morales, Giorgio, et al.
Published: (2025)

Fast Symbolic Regression Benchmarking
by: Martinek, Viktor
Published: (2025)

Equality Graph Assisted Symbolic Regression
by: de Franca, Fabricio Olivetti, et al.
Published: (2025)

Bayesian Symbolic Regression for Missing Physics
by: Strouwen, Arno
Published: (2026)

Breaking the Simplification Bottleneck in Amortized Neural Symbolic Regression
by: Saegert, Paul, et al.
Published: (2026)

Bayesian Symbolic Regression via Posterior Sampling
by: Bomarito, Geoffrey F., et al.
Published: (2025)

Symbolic Regression via Latent Iterative Refinement
by: Chu, Xieting, et al.
Published: (2026)

Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization
by: Deng, Jiaxin, et al.
Published: (2024)

Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks
by: Shmuel, Assaf, et al.
Published: (2023)

SRLR: Symbolic Regression based Logic Recovery to Counter Programmable Logic Controller Attacks
by: Zhou, Hao, et al.
Published: (2025)

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression
by: Crawshaw, Michael, et al.
Published: (2025)

SABER: Symbolic Regression-based Angle of Arrival and Beam Pattern Estimator
by: Chou, Shih-Kai, et al.
Published: (2025)

Scaling Up Diffusion and Flow-based XGBoost Models
by: Cresswell, Jesse C., et al.
Published: (2024)

Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
by: Saveliev, Evgeny S., et al.
Published: (2026)

Improving Genetic Programming for Symbolic Regression with Equality Graphs
by: de Franca, Fabricio Olivetti, et al.
Published: (2025)

Scalable Neural Symbolic Regression using Control Variables
by: Chu, Xieting, et al.
Published: (2023)

Parallel Affine Transformation Tuning of Markov Chain Monte Carlo
by: Schär, Philip, et al.
Published: (2024)

The Syntax and Semantics of einsum
by: Wenig, Maurice, et al.
Published: (2025)

ISR: Invertible Symbolic Regression
by: Tohme, Tony, et al.
Published: (2024)

Multi-View Symbolic Regression
by: Russeil, Etienne, et al.
Published: (2024)

Explaining the Explainer: Understanding the Inner Workings of Transformer-based Symbolic Regression Models
by: van Breda, Arco, et al.
Published: (2026)

Exhaustive Symbolic Regression
by: Bartlett, Deaglan J., et al.
Published: (2022)

Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors
by: Huang, Sikai, et al.
Published: (2025)

Deep Variational Inference Symbolic Regression
by: Butterworth, James, et al.
Published: (2026)

Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement Learning
by: Sun, Chenglu, et al.
Published: (2025)

A Transformer Model for Symbolic Regression towards Scientific Discovery
by: Lalande, Florian, et al.
Published: (2023)

A Comparative Study of Model Selection Criteria for Symbolic Regression
by: Soltani, Ali, et al.
Published: (2026)

An Efficient and Generalizable Symbolic Regression Method for Time Series Analysis
by: Xie, Yi, et al.
Published: (2024)

Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing
by: Martinek, Viktor, et al.
Published: (2026)

Operator Feature Neural Network for Symbolic Regression
by: Deng, Yusong, et al.
Published: (2024)