Results 201 to 210 of about 150,984 (329)

Hybrid Symbolic Regression for Data-Driven Discovery:Governing Dimensionless Numbers in Supercritical Heat Transfer

Yunzhi Shi, Meiqi Song, Hsiaotao T. Bi, Wei Xu, Xiaojing Liu   +4 more
openalex   +1 more source

Expressive Symbolic Regression for Interpretable Models of Discrete-Time Dynamical Systems [PDF]

Adarsh Iyer, Nibodh Boddupalli, Jeff Moehlis   +2 more
openalex   +1 more source

Knowledge integration for physics-informed symbolic regression using pre-trained large language models. [PDF]

Sci Rep
Taskin B, Xie W, Lazebnik T.
europepmc   +1 more source

Identifying interactions in omics data for clinical biomarker discovery using symbolic regression. [PDF]

Bioinformatics, 2022
Christensen NJ, Demharter S, Machado M, Pedersen L, Salvatore M, Stentoft-Hansen V, Iglesias MT.   +6 more
europepmc   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Development of novel symbolic regression models for prediction of nano filters efficiency using CFD and DPM. [PDF]

Sci Rep
Taghavi A, Farahani SD.
europepmc   +1 more source

Combining symbolic regression with the Cox proportional hazards model improves prediction of heart failure deaths. [PDF]

BMC Med Inform Decis Mak, 2022
Wilstrup C, Cave C.
europepmc   +1 more source

Artificial Intelligence Powers Protein Functional Annotation

Advanced Science, EarlyView.
This review systematically summarizes how artificial intelligence advances protein functional annotation. It organizes existing methods into six unified modeling paradigms and analyzes their applications in Gene Ontology and Enzyme Commission prediction.
Wenkang Wang, Qiurong Yang, Min Zeng, Ruiqing Zheng, Min Li   +4 more
wiley   +1 more source

SR-LLM: An incremental symbolic regression framework driven by LLM-based retrieval-augmented generation. [PDF]

Proc Natl Acad Sci U S A
Guo Z, Wang S, Tian Y, Yang J, Yu H, Na X, Kovács L, Li L, Ioannou PA, Wang FY.   +9 more
europepmc   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source