Cover Image

Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Matsubara, Yoshitomo, Chiba, Naoya, Igarashi, Ryo, Ushiku, Yoshitaka
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Artificial Intelligence Neural and Evolutionary Computing Symbolic Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Symbolic Regression with a Learned Concept Library
by: Grayeli, Arya, et al.
Published: (2024)

Enes Causal Discovery
by: Kafantaris, Alexis
Published: (2026)

Symbolic Regression with Multimodal Large Language Models and Kolmogorov Arnold Networks
by: Harvey, Thomas R., et al.
Published: (2025)

Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics
by: Hayes, Conor F., et al.
Published: (2025)

X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning
by: Shiraishi, Hiroki, et al.
Published: (2025)

Guiding Genetic Programming with Graph Neural Networks
by: Wyrwiński, Piotr, et al.
Published: (2024)

Looking Through Glass Box
by: Kafantaris, Alexis
Published: (2026)

Evolutionary Causal Discovery with Relative Impact Stratification for Interpretable Data Analysis
by: Deng, Ou, et al.
Published: (2024)

Symbolic Discovery of Stochastic Differential Equations with Genetic Programming
by: de Vries, Sigur, et al.
Published: (2026)

TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming
by: Kalkreuth, Roman, et al.
Published: (2025)

Artificial Intelligence Software Structured to Simulate Human Working Memory, Mental Imagery, and Mental Continuity
by: Reser, Jared Edward
Published: (2022)

Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation
by: Song, Sum Kyun, et al.
Published: (2026)

High-resolution spatial memory requires grid-cell-like neural codes
by: Cotteret, Madison, et al.
Published: (2025)

Decoupling Representation and Learning in Genetic Programming: the LaSER Approach
by: Le, Nam H., et al.
Published: (2025)

Improving Evaluation of Recombination-based Cartesian Genetic Programming
by: Tran, Duy Long, et al.
Published: (2026)

Learning Guided Automated Reasoning: A Brief Survey
by: Blaauwbroek, Lasse, et al.
Published: (2024)

Learning Conjecturing from Scratch
by: Gauthier, Thibault, et al.
Published: (2025)

Polyra Swarms: A Shape-Based Approach to Machine Learning
by: Klüttermann, Simon, et al.
Published: (2025)

Architecture-Induced Recoverability Bias in Differentiable Symbolic Regression
by: Gupta, Chakshu, et al.
Published: (2026)

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

Mechanisms of Symbol Processing for In-Context Learning in Transformer Networks
by: Smolensky, Paul, et al.
Published: (2024)

A Remedy to Compute-in-Memory with Dynamic Random Access Memory: 1FeFET-1C Technology for Neuro-Symbolic AI
by: Yin, Xunzhao, et al.
Published: (2024)

Memory as Resonance: A Biomimetic Architecture for Infinite Context Memory on Ergodic Phonetic Manifolds
by: Houichime, Tarik, et al.
Published: (2025)

LLM-Meta-SR: In-Context Learning for Evolving Selection Operators in Symbolic Regression
by: Zhang, Hengzhe, et al.
Published: (2025)

Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science
by: Yu, Runlong, et al.
Published: (2025)

Neuro-Symbolic Activation Discovery: Transferring Mathematical Structures from Physics to Ecology for Parameter-Efficient Neural Networks
by: Hajbi, Anas
Published: (2026)

LLM-SR: Scientific Equation Discovery via Programming with Large Language Models
by: Shojaee, Parshin, et al.
Published: (2024)

EGG-SR: Embedding Symbolic Equivalence into Symbolic Regression via Equality Graph
by: Jiang, Nan, et al.
Published: (2025)

Interpretable Neural-Symbolic Concept Reasoning
by: Barbiero, Pietro, et al.
Published: (2023)

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

ViSymRe: Vision Multimodal Symbolic Regression
by: Li, Da, et al.
Published: (2024)

Spacer: Towards Engineered Scientific Inspiration
by: Lee, Minhyeong, et al.
Published: (2025)

Deep Neural Regression Collapse
by: Rangamani, Akshay, et al.
Published: (2026)

Mechanistic Neural Networks for Scientific Machine Learning
by: Pervez, Adeel, et al.
Published: (2024)

NNGPT: Rethinking AutoML with Large Language Models
by: Kochnev, Roman, et al.
Published: (2025)

CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models
by: Guo, Ping, et al.
Published: (2024)

Auditable Unit-Aware Thresholds in Symbolic Regression via Logistic-Gated Operators
by: Deng, Ou, et al.
Published: (2025)

Average-Over-Time Spiking Neural Networks for Uncertainty Estimation in Regression
by: Sun, Tao, et al.
Published: (2024)

Contrastive Concept-Tree Search for LLM-Assisted Algorithm Discovery
by: Leleu, Timothee, et al.
Published: (2026)

AutoQD: Automatic Discovery of Diverse Behaviors with Quality-Diversity Optimization
by: Hedayatian, Saeed, et al.
Published: (2025)