Results 231 to 240 of about 1,858,266 (298)

Quantum‐Trained AI Enables Inverse Design of Organic Frontier Orbitals at Billion‐Scale

Advanced Science, EarlyView.
Quantum‐trained AI links molecular substructures to frontier‐orbital energetics and enables interpretable screening across nearly one billion GDB‐13 molecules. By combining fragment‐ and ring‐level insights with donor–acceptor energy alignment against ITIC, the framework narrows an immense chemical space to a small set of promising candidates and ...
Yeongnam Ko, Se Jin Kim, Ki Chul Kim
wiley   +1 more source

Automated deep learning by recurrent hyperparameter optimization. [PDF]

Nat Commun
Cheng Z, Cheng Y, Zhang C, Li X, Guan J, Wu F, Zhou S.   +6 more
europepmc   +1 more source

Predicting Single‐Cell Perturbation Responses Across Biological Contexts With a Deep Generative Model Integrating Optimal Transport

Advanced Science, EarlyView.
Single‐cell perturbation responses are predicted across held‐out biological contexts using scPILOT, a query‐conditioned two‐stage latent response‐transfer framework. A shared latent representation supports cell‐level response estimation by latent optimal transport, followed by Leiden‐localized query‐specific transfer and adaptive weighting.
Jialiang Wang, Ziqi Liu, Zhengqian Zhang, Yikun Cao, Junjun Ren, Peng Cheng, Jingjing Tian, Lingyun Xie, Xin Lu, Zhanwei Du, Yongzhuang Liu   +10 more
wiley   +1 more source

Developing machine learning regression model optimized using Tabu search harmony search algorithm for prediction of mass transfer in membranes. [PDF]

Sci Rep
Abu-Hamdeh NH, Milyani AH, Almitani KH.
europepmc   +1 more source

Adaptive Hyperparameter Optimization

This paper introduces an adaptive hyperparameter optimization algorithm designed to enhance model generalization. Traditional hyperparameter optimization methods often employ static strategies, failing to adapt to the intricacies of individual models.
openaire   +1 more source

A Physical Adaptive Material Motor Unit Neural Network: A Hygromorph Composite Material Machine

Advanced Science, EarlyView.
This study introduces a new class of material‐based intelligent machines. It presents a Physical Adaptive Material Motor Unit Neural Network, an assembly of smart 4D printed actuators and a controlling system that adapt through environmental interaction its shading behavior.
Charles de Kergariou, Helmut Hauser, David Correa   +2 more
wiley   +1 more source

Robots and Minimal, Physics‐Informed Features: A Hybrid Framework for Enzyme Catalysis

Advanced Science, EarlyView.
Robotic experimentation and physics‐informed machine learning combine to predict enzyme substrate scope. With a handful of interpretable features derived from docking and quantum mechanics calculations, our model rivals descriptor‐heavy AI approaches and extrapolates to unseen substrates and enzyme classes.
Natalia Onishchenko, Eric S. Larsen, Govind Paneru, Kisung Lee, Diana V. Kolygina, Yankai Jia, Elizabeth Maria Clarissa, Wai‐Shing Wong, Bartosz A. Grzybowski   +8 more
wiley   +1 more source

An Optimized and Explainable Machine Learning Framework for Diabetes Prediction Using Marine Predators Algorithm and SHAP. [PDF]

J Pers Med
Nasrin A, Asif MB, Naidu R, Asif AH, Chohan MS, Khan GA, Arifuzzaman M, Azad A, Martuza MA.   +8 more
europepmc   +1 more source

A Dual‐Mode In Situ EV‐miRNA Profiling Platform for Machine‐Learning‐Assisted Gastric Cancer Liquid Biopsy

Advanced Science, EarlyView.
An in situ dual‐mode platform integrates fusogenic liposomes with localized autocatalytic DNA circuits for plasma‐derived extracellular vesicle microRNA analysis. Following membrane fusion, target miRNAs trigger feedback‐assisted LECHA amplification inside intact vesicles, generating fluorescence and electrochemical outputs. Machine learning integrates
Wenbin Li, Rui Fan, Kun Xie, Jiehua Zhong, Yitong Zhu, Tingting Ji, Yuanyuan Qin, Shijin Peng, Yu Zhang, Yuhang Guo, Tiange Zhang, Chunchen Liu, Bo Li, Lei Zheng, Ye Zhang, Xiaohui Yan   +15 more
wiley   +1 more source