Results 121 to 130 of about 1,651,457 (304)

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Establishing a New Link between Fuzzy Logic, Neuroscience, and Quantum Mechanics through Bayesian Probability: Perspectives in Artificial Intelligence and Unconventional Computing. [PDF]

Molecules, 2021
Gentili PL.
europepmc   +1 more source

Multi‐Omics Profiling of High‐Grade Serous Ovarian Cancer Reveals an Inflammation‐Related Lipid Metabolism Subtype Associated With Platinum Resistance

Advanced Science, EarlyView.
Through integrated proteomic and metabolomic profiling, Zhao et al. identified three molecular subtypes of high‐grade serous ovarian cancer. The high‐risk subtype exhibits activated arachidonic acid metabolism and cyclooxygenase‐2 overexpression. This metabolic axis promotes M2‐like macrophage infiltration, which contributes to platinum resistance ...
Yuxi Zhao, Junyi Li, Bo Zheng, Wanshan Liu, Yaru Wang, Shufeng Wang, Ying Cui, Huiqin Guo, Hongxia Wang, Ting Xiao, Kun Qian, Jing Zuo   +11 more
wiley   +1 more source

StackingNet: Collective Inference Across Independent AI Foundation Models

Advanced Science, EarlyView.
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li, Chenhao Liu, Dongrui Wu, Zhigang Zeng, Lieyun Ding   +4 more
wiley   +1 more source

Bayesian Probabilities and Quartet Puzzling [PDF]

Molecular Biology and Evolution, 1997
Strimmer, K, Goldman, N, von Haeseler, Arndt   +2 more
openaire   +3 more sources

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

Advanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford, Matthew Tamasi, Elena Di Mare, Adam J. Gormley   +3 more
wiley   +1 more source

The use of Bayesian methods for the analysis of Studies Within A Trial: a proof-of-concept case study

Trials
Background and Aims A Study Within A Trial (SWAT) is a research study embedded within a larger trial which aims to investigate different strategies for a particular trial process, such as trial recruitment.
Suzie Cro, Zhangyi He, Daphne Babalis, Laurent Billot   +3 more
doaj   +1 more source

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

Advanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park, Yeongje Lee, Sunho Jeong, Eungkyu Lee   +3 more
wiley   +1 more source

Uncertainty Forecasting Model for Mountain Flood Based on Bayesian Deep Learning

IEEE Access
Due to the characteristics of strong suddenness, high harmfulness, and frequent occurrence of mountain flood disasters in small watersheds, the accuracy and reliability of mountain flood forecasting are insufficient in small watersheds.
Songsong Wang, Ouguan Xu
doaj   +1 more source