Results 71 to 80 of about 898,588 (270)
Accelerated Discovery of High Performance Ni3S4/Ni3Mo HER Catalysts via Bayesian Optimization
Advanced Functional Materials, EarlyView.Integrated workflow accelerates the catalyst discovery of hydrogen evolution reaction via Bayesian optimization. An experiment‐trained surrogate model proposes synthesis conditions, guiding iterative refinement using electrochemical performance metrics.
Namuersaihan Namuersaihan +9 more
wiley +1 more source
Hierarchical Bayesian reliability assessment of energy networks
Lietuvos Matematikos Rinkinys, 2015 It is often the case that data used for the systems reliability assessment comes from more than one information source. Whether they are power plants at different geographical locations, gas transmission pipelines operating in different environment or ...
Tomas Iešmantas, Robertas Alzbutas
doaj +1 more source
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models
, 2015 Learning in deep models using Bayesian methods has generated significant attention recently. This is largely because of the feasibility of modern Bayesian methods to yield scalable learning and inference, while maintaining a measure of uncertainty in the
Carin, Lawrence +3 more
core +1 more source
Artificial Intelligence as the Next Visionary in Liquid Crystal Research
Advanced Functional Materials, EarlyView.The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam +2 more
wiley +1 more source
Bayesian Methods for Medical Test Accuracy
Diagnostics, 2011 Bayesian methods for medical test accuracy are presented, beginning with the basic measures for tests with binary scores: true positive fraction, false positive fraction, positive predictive values, and negative predictive value. The Bayesian approach is
Lyle D. Broemeling
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On computational tools for Bayesian data analysis
, 2010 While Robert and Rousseau (2010) addressed the foundational aspects of Bayesian analysis, the current chapter details its practical aspects through a review of the computational methods available for approximating Bayesian procedures.
Marin, Jean-Michel, Robert, Christian P.
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Bayesian optimization for materials design
, 2015 We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets.
A Booker +28 more
core +1 more source
Advanced Healthcare Materials, EarlyView.We developed a micro‐sized, biocompatible implant for postoperative sustained delivery of anti‐fibrotic antibodies in glaucoma surgery. Machine learning‐guided optimization of polymer composition, implant geometry, and porosity enabled precise control of drug release.
Mengqi Qin +5 more
wiley +1 more source
Quantum Measurement and Weak Values in Entropic Dynamics
, 2017 The problem of measurement in quantum mechanics is studied within the Entropic Dynamics framework. We discuss von Neumann and Weak measurements, wavefunction collapse, and Weak Values as examples of bayesian and entropic inference.Comment: Presented at ...
Caticha, Ariel, Vanslette, Kevin
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Isolation Defines Identity: Functional Consequences of Extracellular Vesicle Purification Strategies
Advanced Healthcare Materials, EarlyView.Four extracellular vesicle purification strategies are compared using ovarian‐cancer ascites and ES‐2 cell supernatants. A novel workflow links purification to function by combining particle‐normalized proteomics with matched cell‐free and cell‐based assays.
Christian Preußer +10 more
wiley +1 more source