Results 121 to 130 of about 67,103 (261)
On the asymptotics of random forests
The last decade has witnessed a growing interest in random forest models which are recognized to exhibit good practical performance, especially in high-dimensional settings. On the theoretical side, however, their predictive power remains largely unexplained, thereby creating a gap between theory and practice. The aim of this paper is twofold. Firstly,
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Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei +9 more
wiley +1 more source
Mesoporous Silica Nanoparticles in Biomedicine: Advances and Prospects
Mesoporous silica nanoparticles offer unique properties like high surface area, tunable pores, and functionalization. They excel in drug delivery, tissue engineering, and stimuli‐responsive therapies, enabling targeted and controlled treatments. With roles in cancer therapy and diagnostics, their clinical translation requires addressing challenges in ...
Miguel Manzano, María Vallet‐Regí
wiley +1 more source
Opportunities of Semiconducting Oxide Nanostructures as Advanced Luminescent Materials in Photonics
The review discusses the challenges of wide and ultrawide bandgap semiconducting oxides as a suitable material platform for photonics. They offer great versatility in terms of tuning microstructure, native defects, doping, anisotropy, and micro‐ and nano‐structuring. The review focuses on their light emission, light‐confinement in optical cavities, and
Ana Cremades +7 more
wiley +1 more source
Stand spatial structure plays a key role in forest management, and in particular the random structural unit, comprising random tree and its neighbors, largely determines forest stability and its productivity.
Jing Zhang +3 more
doaj +1 more source
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
In many domains, repeated measurements are systematically collected to obtain the characteristics of objects or situations that evolve over time or other logical orderings. Although the classification of such data series shares many similarities with traditional multidimensional classification, inducing accurate machine learning models using ...
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Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
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Yohei Mishina +2 more
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Can Elastomers Combine Stiffness, Toughness and Fatigue Resistance?
This review studies how the molecular and macroscopic architecture of elastomers influence their mechanical properties including: stiffness, stretchability, toughness, fatigue resistance, and damping behavior. By linking the structure to performance, it proposes design principles for advanced elastomeric systems that combine mechanical properties ...
Eva Baur, Esther Amstad
wiley +1 more source

