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#symbolic-regression

3 curated events
papersTODAY 04:00 UTC

Physics-Regularized Symbolic Modeling of 3nm FinFETs via Universal Differential Equations

A new arXiv preprint presents PRISM-UDE, a method that blends universal differential equations with physics-based regularization to build compact models of 3nm FinFET transistors. Hand-derived compact models struggle to capture transport behavior at advanced nodes, while purely data-driven neural surrogates can sacrifice physical consistency. The approach aims to yield interpretable, equation-based device models suitable for circuit simulation.

semiconductors/physics-informed/symbolic-regression/arxiv
papersTODAY 04:00 UTC

Symbolic regression estimates neutron-star radii from gravitational-wave data alone

A new arXiv preprint explores using symbolic regression to infer neutron-star radii from gravitational-wave signals emitted during binary neutron-star inspirals. Such signals directly constrain component masses and tidal deformabilities, but radii are normally obtained through electromagnetic observations. The approach aims to support multi-messenger studies by deriving radius estimates without relying on electromagnetic data.

symbolic-regression/gravitational-waves/astrophysics/arxiv
papersSEP 12 04:00 UTC

LLMs as Post-hoc Auditors of Physiological Plausibility in Symbolic Regression

A new arXiv paper examines whether large language models can serve as post-hoc reviewers that judge whether equations produced by symbolic regression are physiologically sensible. The study uses genetic programming and grammatical evolution to derive mathematical expressions from multivariate data, then has clinicians evaluate the LLM assessments. It is a case study rather than a benchmark, focusing on plausibility screening alongside predictive accuracy.

symbolic-regression/llm-evaluation/healthcare/research