Results 111 to 120 of about 110,828 (307)

Gaussian Semiparametric Estimation of Non-stationary Time Series [PDF]

, 1998
Generalizing the definition of the memory parameter d in terms of the differentiated series, we showed in Velasco (Non-stationary log-periodogram regression, Forthcoming J.
Velasco Gómez, Carlos, Velasco, Carlos
core  

Solving Dynamic Traveling Salesman Problem Using Dynamic Gaussian Process Regression

Journal of Applied Mathematics, 2014
This paper solves the dynamic traveling salesman problem (DTSP) using dynamic Gaussian Process Regression (DGPR) method. The problem of varying correlation tour is alleviated by the nonstationary covariance function interleaved with DGPR to generate a ...
Stephen M. Akandwanaho, Aderemi O. Adewumi, Ayodele A. Adebiyi   +2 more
doaj   +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

Invariances for Gaussian models [PDF]

, 2015
At the heart of a statistical analysis, we are interested in drawing conclusions about random variables and the laws they follow. For this we require a sample, therefore our approach is best described as learning from data.
Adametz, David
core   +1 more source

AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing

Advanced Materials, EarlyView.
This work presents an artificial intelligence (AI)‐guided 4D‐printed microneedle platform inspired by carnivorous plants for wound healing. A thermo‐responsive shape memory polymer enables body temperature–triggered self‐coiling for autonomous wound closure.
Hyun Lee, Moon‐Jo Kim, DongEung Kim, Chan Ho Moon, Seojoon Bang, Hyeong Seok Kang, Ju Yeong Gwon, Jong Hwa Seo, Junhyub Jeon, Junhyuk Son, Munwon Lim, Minho Kang, Dong Yun Lee, Donghyun Lim, Jung‐Hoon Park, Gi Doo Cha, Soo‐Hong Lee, Tae‐Sik Jang, Kisuk Yang, Yunho Jeong, Youngho Eom, Hyun‐Do Jung   +21 more
wiley   +1 more source

Forecasting Evaporative Loss by Least-Square Support-Vector Regression and Evaluation with Genetic Programming, Gaussian Process, and Minimax Probability Machine Regression: Case Study of Brisbane City

, 2017
Daily evaporative loss (EpEp) forecasting models are decisive tools with potential applications in hydrology, the design of water systems, urban water assessments, and irrigation management. This paper performs a case study for forecasting daily EpEp for
Deo, Ravinesh C., Samui, Pijush, Ravinesh C. Deo, Pijush Samui   +3 more
core   +1 more source

A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series [PDF]

, 2010
Understanding the regulatory mechanisms that are responsible for an organism's response to environmental change is an important issue in molecular biology.
Cooke, Emma J., Wild, D.L., Stegle, O, Cooke, EJ, Denby, K., Denby, Katherine J., Cooke, E.J., Denby, K. J., Ghahramani, Z, Wild, D. L., Borgwardt, KM, Wild, D., Wild, David L., Borgwardt, K.M., Cooke, E., Borgwardt, K. M., Ghahramani, Z., ,, Stegle, Oliver, Borgwardt, Karsten M., Wild, DL, Cooke, E. J., Stegle, O., Ghahramani, Zoubin, Borgwardt, K., Denby, KJ, Denby, K.J.   +26 more
core   +1 more source

Quantum Gaussian process regression

, 2021
In this paper, a quantum algorithm based on gaussian process regression model is proposed. The proposed quantum algorithm consists of three sub-algorithms. One is the first quantum subalgorithm to efficiently generate mean predictor.
Lin, Song, Guo, Gongde, Li, Jing, Chen, Menghan   +3 more
core   +2 more sources

Gaussian Processes For Regression In Channel Equalization

, 2006
Publication in the conference proceedings of EUSIPCO, Florence, Italy ...
Sebastian Caro, Fernando Pérez-Cruz, Juan José Murillo-Fuentes   +2 more
openaire   +4 more sources

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