Results 171 to 180 of about 43,440 (267)

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

Co-morbidity of malaria and soil-transmitted helminths in Nigeria: a joint Bayesian modelling approach. [PDF]

Infect Dis Poverty
Eshofonie F, Johnson O, Gayawan E.
europepmc   +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

Spatial-temporal risk of Opisthorchis felineus infection in Western Siberia and the Ural Region of Russian Federation: a joint Bayesian modelling study based on survey and surveillance data. [PDF]

Infect Dis Poverty
Zhang WL, Zeng YH, Lai YS.
europepmc   +1 more source

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

Bayesian modelling disentangles language versus executive control disruption in stroke. [PDF]

Brain Commun
Hartwigsen G, Lim JS, Bae HJ, Yu KH, Kuijf HJ, Weaver NA, Biesbroek JM, Kopal J, Bzdok D.   +8 more
europepmc   +1 more source

Bayesian modelling of nonlinear Poisson regression with artificial neural networks. [PDF]

J Appl Stat, 2020
Rodrigo H, Tsokos C.
europepmc   +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

Bayesian modelling of time series data (BayModTS)-a FAIR workflow to process sparse and highly variable data. [PDF]

Bioinformatics
Höpfl S, Albadry M, Dahmen U, Herrmann KH, Kindler EM, König M, Reichenbach JR, Tautenhahn HM, Wei W, Zhao WT, Radde NE.   +10 more
europepmc   +1 more source

Using a Bayesian modelling approach (INLA-SPDE) to predict the occurrence of the Spinetail Devil Ray (Mobular mobular). [PDF]

Sci Rep, 2020
Lezama-Ochoa N, Pennino MG, Hall MA, Lopez J, Murua H.   +4 more
europepmc   +1 more source