Results 71 to 80 of about 3,284,626 (292)

Intelligent Tutoring Systems by Bayesian Nets with Noisy Gates

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022
Directed graphical models such as Bayesian nets are often used to implement intelligent tutoring systems able to interact in real-time with learners in a purely automatic way.
Alessandro Antonucci, Francesca Mangili, Claudio Bonesana, Giorgia Adorni   +3 more
doaj   +1 more source

Grayscale Photomasks Enable Noncontact Optical Patterning of Hydroxypropyl Cellulose Gels for Dynamic Art

Advanced Functional Materials, EarlyView.
Mask‐encoded UV exposure translates digital color information into pixel‐resolved structural‐color patterns in hydroxypropyl cellulose gels. Gaussian‐process‐guided calibration links UV processing conditions, wavelength, and mask opacity, enabling parallel fabrication of multicolor images in a single 10 s exposure.
Mengting Ye, Yunyi Zhu, Sai Sabareesh KS, Md Ashiqur Rahman Alif, Yichen Wan, Ruobing Bai, Narges Pourjafarian, Stefanie Mueller, Hongli Zhu   +8 more
wiley   +1 more source

Uniqueness of the Level Two Bayesian Network Representing a Probability Distribution

International Journal of Mathematics and Mathematical Sciences, 2011
Bayesian Networks are graphic probabilistic models through which we can acquire, capitalize on, and exploit knowledge. they are becoming an important tool for research and applications in artificial intelligence and many other fields in the last decade ...
Linda Smail
doaj   +1 more source

Reasoning over Bayesian Networks using Semantic Artificial Neural Networks

, 2021
Representation of application domains, related concepts and their dependencies is often achieved using Bayesian Networks. In Bayesian Networks nodes represent random variables and arcs represent their dependencies.
Batsakis, Sotirios, Sotirios Batsakis, Antoniou, G, Antoniou, Grigoris, Grigoris Antoniou, Batsakis, S, Μπατσακης Σωτηριος(http://users.isc.tuc.gr/~sbatsakis), Batsakis Sotirios(http://users.isc.tuc.gr/~sbatsakis), Antoniou, Grigoris(https://viaf.org/viaf/85475721)   +8 more
core   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

CausalTrail: Testing hypothesis using causal Bayesian networks [version 1; referees: 2 approved]

F1000Research, 2015
Summary Causal Bayesian Networks are a special class of Bayesian networks in which the hierarchy directly encodes the causal relationships between the variables. This allows to compute the effect of interventions, which are external changes to the system,
Daniel Stöckel, Florian Schmidt, Patrick Trampert, Hans-Peter Lenhof   +3 more
doaj   +1 more source

Searching multiregression dynamic models of resting-state fMRI networks using integer programming [PDF]

, 2015
A Multiregression Dynamic Model (MDM) is a class of multivariate time series that represents various dynamic causal processes in a graphical way. One of the advantages of this class is that, in contrast to many other Dynamic Bayesian Networks, the ...
Smith, Jim, Cussens, James, Duff, Eugene P., Nichols, Thomas, Makin, Tamar, Costa, Lilia, Smith, J. Q., Duff, Eugene, Makin, Tamar R., Nichols, Thomas E.   +9 more
core   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
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

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
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, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source