Results 111 to 120 of about 374,385 (274)

Scaling Gaussian Process Regression with Derivatives

CoRR, 2018
Appears at Advances in Neural Information Processing Systems 32 (NIPS ...
David Eriksson, Kun Dong, Eric Hans Lee, David Bindel, Andrew Gordon Wilson   +4 more
openaire   +3 more sources

Unveiling the Role of Curvature in Carbon for Improved Energy Release of Ammonium Perchlorate

Advanced Materials, EarlyView.
High‐curvature carbon materials identified via machine learning and simulation can enhance the heat release and combustion performance of ammonium perchlorate. ABSTRACT The catalytic role of carbon curvature in the thermal decomposition of ammonium perchlorate (AP) remains largely unexplored. To address this gap, this study employs machine learning and
Dan Liu, Keliang Song, Haorui Zhang, Zhipeng Liu, Guansong He, Junru Wang, Wenming Yang, Xu Zhao, Zhijian Yang   +8 more
wiley   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Link quality prediction model based on Gaussian process regression

Tongxin xuebao, 2018
Link quality is an important factor of reliable communication and the foundation of upper protocol design for wireless sensor network.Based on this,a link quality prediction model based on Gaussian process regression was proposed.It employed grey ...
Jian SHU, Manlan LIU, Yaqing SHANG, Yubin CHEN, Linlan LIU   +4 more
doaj   +2 more sources

Gaussian Process Regression with Measurement Error

IEICE Transactions on Information and Systems, 2010
Regression analysis that incorporates measurement errors in input variables is important in various applications. In this study, we consider this problem within a framework of Gaussian process regression. The proposed method can also be regarded as a generalization of kernel regression to include errors in regressors.
Yukito Iba, Shotaro Akaho
openaire   +2 more sources

Mixed‐Metal Promotion in a Manganese‐Molybdenum Oxynitride as Catalyst to Integrate C─C and C─N Coupling Reactions for the Direct Synthesis of Acetonitrile from Syngas and Ammonia

Advanced Materials, EarlyView.
Transition metal oxy/carbo‐nitrides show great promise as catalysts for sustainable processes. A Mn‐Mo mixed‐metal oxynitride attains remarkable performance for the direct synthesis of acetonitrile, an important commodity chemical, via sequential C─N and C─C coupling from syngas (C1) and ammonia (N1) feedstocks.
M. Elena Martínez‐Monje, Wilson Henao, Tania Rodenas, Patricia Concepción, Virginia Pérez Dieste, Alexander Missyul, Giovanni Agostini, Gonzalo Prieto   +7 more
wiley   +1 more source

Kelvin Probe Force Microscopy in Bionanotechnology: Current Advances and Future Perspectives

Advanced Materials, EarlyView.
Kelvin probe force microscopy (KPFM) enables the nanoscale mapping of electrostatic surface potentials. While widely applied in materials science, its use in biological systems remains emerging. This review presents recent advances in KPFM applied to biological samples and provides a critical perspective on current limitations and future directions for
Ehsan Rahimi, Mario Palacios‐Corella, Arjan Mol, Salvador Pané, Josep Puigmartí‐Luis   +4 more
wiley   +1 more source

Multivariate Interpolation of Wind Field Based on Gaussian Process Regression

Atmosphere, 2018
The resolution of the products of numerical weather prediction is limited by the resolution of numerical models and computing resources, which can be improved accurately by a well-chosen interpolation algorithm.
Miao Feng, Weimin Zhang, Xiangru Zhu, Boheng Duan, Mengbin Zhu, De Xing   +5 more
doaj   +1 more source

Proper Complex Gaussian Processes for Regression

CoRR, 2015
Complex-valued signals are used in the modeling of many systems in engineering and science, hence being of fundamental interest. Often, random complex-valued signals are considered to be proper. A proper complex random variable or process is uncorrelated with its complex conjugate.
Rafael Boloix-Tortosa, F. Javier Payan-Somet, Eva Arias-de-Reyna, Juan José Murillo-Fuentes   +3 more
openaire   +2 more sources

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