Tagged articles

symbolic regression

5 articles · Page 1 of 1

Machine Learning Algorithms & Natural Language Processing

Aug 11, 2026 · Artificial Intelligence

Bengio Team’s ERRLESS Boosts Symbolic Regression with 10× Faster Posterior Sampling

The paper introduces ERRLESS, a Bayesian symbolic regression framework that reformulates posterior sampling as a maximum‑entropy reinforcement‑learning problem, achieving ten‑fold speedups, robust noise handling, and state‑of‑the‑art performance on Feynman and Blackbox benchmarks.

AI researchGFlowNetbayesian inference

0 likes · 10 min read

Bengio Team’s ERRLESS Boosts Symbolic Regression with 10× Faster Posterior Sampling

Machine Heart

Jun 19, 2026 · Artificial Intelligence

LLMs Finally Derive Formulas: FunctionEvolve Boosts LLM‑SRBench Accuracy 3.6× and Scores Perfect on AI‑Feynman

The FunctionEvolve framework represents formulas as abstract syntax trees, letting large language models guide symbolic regression; this yields a 3.6‑fold improvement on the LLM‑SRBench benchmark (55.8% SA@1) and a perfect 120/120 score on AI‑Feynman, with detailed component ablations confirming the value of structure‑aware generation, selection, mutation, and optimization.

AI‑FeynmanASTFunctionEvolve

0 likes · 15 min read

LLMs Finally Derive Formulas: FunctionEvolve Boosts LLM‑SRBench Accuracy 3.6× and Scores Perfect on AI‑Feynman

Bighead's Algorithm Notes

May 29, 2026 · Artificial Intelligence

AlphaCFG: Grammar‑Guided, Interpretable Alpha‑Factor Discovery Framework

AlphaCFG introduces a grammar‑based framework that defines a controllable search space for discovering syntactically valid, financially interpretable alpha factors, using syntax‑aware Monte‑Carlo tree search guided by value and policy networks, and demonstrates superior search efficiency and profitability on Chinese and US stock datasets.

Grammar Guided SearchMonte Carlo Tree Searchalpha factor

0 likes · 17 min read

AlphaCFG: Grammar‑Guided, Interpretable Alpha‑Factor Discovery Framework

AI Agent Research Hub

Apr 2, 2026 · Artificial Intelligence

Constrained Symbolic Regression and Weak Form Uncover Laws from Noisy Incomplete Data

By integrating universal physical symmetries, weak‑form integral transformations, and sparse symbolic regression, the authors devise a hybrid framework that extracts governing Navier‑Stokes equations from high‑dimensional, noisy, and partially observed fluid experiments, while also reconstructing hidden pressure and Lorentz force fields.

Navier-Stokesfluid dynamicslatent variables

0 likes · 12 min read

Constrained Symbolic Regression and Weak Form Uncover Laws from Noisy Incomplete Data

Code Mala Tang

Oct 9, 2025 · Artificial Intelligence

Discover 10 Underrated Machine Learning Algorithms That Can Supercharge Your Models

This article explores several powerful yet often overlooked machine‑learning techniques—including symbolic regression, isolation forest, Tsetlin machines, random kitchen sinks, field‑aware factorization machines, CRFs, ELMs, and VAEs—detailing their principles, code implementations, and real‑world application scenarios.

AlgorithmsIsolation ForestMachine Learning

0 likes · 23 min read

Discover 10 Underrated Machine Learning Algorithms That Can Supercharge Your Models