Results 221 to 230 of about 549,710 (321)

Incorporating uncertainty in Indigenous sea Country monitoring with Bayesian statistics: Towards more informed decision-making. [PDF]

Ambio
Cure K, Barneche DR, Depczynski M, Fisher R, Warne DJ, McGree J, Underwood J, Weisenberger F, Evans-Illidge E, Ford B, Oades D, Howard A, McCarthy P, Pyke D, Edgar Z, Maher R, Sampi T, Dougal K, Bardi Jawi Traditional Owners.   +18 more
europepmc   +1 more source

Observational constraints using Bayesian statistics and Deep Learning in $f(Q)$ gravity [PDF]

Lokesh Kumar Sharma, Suresh Parekh, Anil K. Yadav   +2 more
openalex   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics [PDF]

, 2017
Florian Härtig, Francesco Minunno, Stefan Paul   +2 more
openalex   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Improving transparency and replication in Bayesian statistics: The WAMBS-Checklist.

, 2015
Sarah Depaoli, Rens van de Schoot
openalex   +2 more sources

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Natural scene statistics and Bayesian natural selection

, 2010
Wilson S. Geisler, R. L. Diehl
openalex   +1 more source