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.

Alpha FactorGrammar Guided SearchMonte Carlo Tree Search

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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-StokesSymbolic Regressionfluid dynamics

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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 ForestSymbolic Regression

0 likes · 23 min read

Discover 10 Underrated Machine Learning Algorithms That Can Supercharge Your Models