Results 101 to 110 of about 8,744,702 (255)
georgestein/ml-in-cosmology: Machine learning in cosmology
, 2020 An attempt to create a comprehensive list of machine learning applications to cosmology, organized by subject matter and arXiv posting date. See https://github.com/georgestein/ml-in-cosmology for the most up-to-date list.
George Stein
core +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Advanced Functional Materials, EarlyView.Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
EXPLORING THE ROLE OF MACHINE LEARNING IN ADVANCING THE SUSTAINABLE DEVELOPMENT AGENDA [PDF]
Proceedings on Engineering SciencesA subset of artificial intelligence (AI), machine learning (ML) has the potential to transform several industries by increasing productivity and encouraging sustainability completely.
Diksha Dalal +2 more
doaj +1 more source
Advanced Functional Materials, EarlyView.This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio +7 more
wiley +1 more source
Fiber‐Based Wearable Electronics as Adaptive Biointerfaces for Healthcare Applications
Advanced Functional Materials, EarlyView.Fiber‐based wearable electronics have been extensively studied as adaptive healthcare biointerfaces. In this review, we classify and introduce fiber‐based systems according to biointerface design, conductive materials, transduction mechanisms, and healthcare applications, and provide a perspective on their translation toward reliable, continuous ...
Sangwoo Hong +5 more
wiley +1 more source
2D Transparency Space—Bring Domain Users and Machine Learning Experts Together
, 2018 Machine Learning (ML) is currently facing prolonged challenges with the user acceptance of delivered solutions as well as seeing system misuse, disuse, or even failure. These fundamental challenges can be attributed to the nature of the “black-box” of ML
Fang Chen +3 more
core +1 more source
Advanced Functional Materials, EarlyView.An organic neuromorphic architecture for the classification of human motor behavior is presented and validated. It performs somatic integration by linearly combining the activity from three muscles. An investigation of synaptic weights is presented and discussed in relationship with the classification performance.
Ilenia Sergi +7 more
wiley +1 more source
On Leveraging Machine Learning in Sport Science in the Hypothetico-deductive Framework
Sports Medicine - OpenSupervised machine learning (ML) offers an exciting suite of algorithms that could benefit research in sport science. In principle, supervised ML approaches were designed for pure prediction, as opposed to explanation, leading to a rise in powerful, but ...
Jordan Rodu +3 more
doaj +1 more source
Prediction of Creep Rupture Life of 5Cr-0.5Mo Steel Using Machine Learning Models
MetalsThe creep rupture life of 5Cr-0.5Mo steels used in high-temperature applications is significantly influenced by factors such as minor alloying elements, hardness, austenite grain size, non-metallic inclusions, service temperature, and applied stress. The
Muhammad Ishtiaq +4 more
doaj +1 more source
Advanced Functional Materials, EarlyView.A degradable, skin‐conformal bioelectronic patch combines a starch‐dominated nanocomposite conductor with a gelatin substrate to enable sensitive strain sensing, high‐fidelity electrocardiography, electromyography, electrooculography, and machine‐learning‐assisted gesture control.
Ming Dong +10 more
wiley +1 more source