Cargando…

Gaussian Process Regression for Materials and Molecules

[Image: see text] We provide an introduction to Gaussian process regression (GPR) machine-learning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of interatomic potentials, or...

Descripción completa

Detalles Bibliográficos
Autores principales:	Deringer, Volker L., Bartók, Albert P., Bernstein, Noam, Wilkins, David M., Ceriotti, Michele, Csányi, Gábor
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Chemical Society 2021
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391963/ https://www.ncbi.nlm.nih.gov/pubmed/34398616 http://dx.doi.org/10.1021/acs.chemrev.1c00022

Ejemplares similares

Machine learning unifies the modeling of materials and molecules
por: Bartók, Albert P., et al.
Publicado: (2017)

Quantifying Chemical Structure and Machine‐Learned Atomic Energies in Amorphous and Liquid Silicon
por: Bernstein, Noam, et al.
Publicado: (2019)

Regression with Gaussian Processes
por: Kalia, Saarik
Publicado: (2016)

Extracting Crystal Chemistry from Amorphous Carbon Structures
por: Deringer, Volker L., et al.
Publicado: (2017)

A general-purpose machine-learning force field for bulk and nanostructured phosphorus
por: Deringer, Volker L., et al.
Publicado: (2020)

Gaussian process regression for ultrasound scanline interpolation
por: Degirmenci, Alperen, et al.
Publicado: (2022)

Towards an atomistic understanding of disordered carbon electrode materials
por: Deringer, Volker L., et al.
Publicado: (2018)

Reactivity of Amorphous Carbon Surfaces: Rationalizing the Role of Structural Motifs in Functionalization Using Machine Learning
por: Caro, Miguel A., et al.
Publicado: (2018)

Splitting Gaussian processes for computationally-efficient regression
por: Terry, Nick, et al.
Publicado: (2021)

Gaussian process regression analysis for functional data
por: Shi, Jian Qing, et al.
Publicado: (2011)

The pitfalls of using Gaussian Process Regression for normative modeling
por: Xu, Bohan, et al.
Publicado: (2021)

Autonomous materials discovery driven by Gaussian process regression with inhomogeneous measurement noise and anisotropic kernels
por: Noack, Marcus M., et al.
Publicado: (2020)

Heteroscedastic sparse Gaussian process regression-based stochastic material model for plastic structural analysis
por: Chen, Baixi, et al.
Publicado: (2022)

Gaussian Process Regression for Data Fulfilling Linear Differential Equations with Localized Sources †
por: Albert, Christopher G., et al.
Publicado: (2020)

Estimation of Clustering Parameters Using Gaussian Process Regression
por: Rigby, Paul, et al.
Publicado: (2014)

Correlated product of experts for sparse Gaussian process regression
por: Schürch, Manuel, et al.
Publicado: (2023)

Accelerating multiscale modelling of fluids with on-the-fly Gaussian process regression
por: Stephenson, David, et al.
Publicado: (2018)

Detecting differential growth of microbial populations with Gaussian process regression
por: Tonner, Peter D., et al.
Publicado: (2017)

Gaussian Process Regression Plus Method for Localization Reliability Improvement
por: Liu, Kehan, et al.
Publicado: (2016)

Prediction of Bus Passenger Traffic using Gaussian Process Regression
por: G S, Vidya, et al.
Publicado: (2022)

Efficient inference of synaptic plasticity rule with Gaussian process regression
por: Chen, Shirui, et al.
Publicado: (2023)

Gaussian Process Regression Models for Predicting Atomic Energies and Multipole Moments
por: Burn, Matthew J., et al.
Publicado: (2023)

Local invertibility and sensitivity of atomic structure-feature mappings
por: Pozdnyakov, Sergey N., et al.
Publicado: (2021)

Robustness of Local Predictions in Atomistic Machine Learning Models
por: Chong, Sanggyu, et al.
Publicado: (2023)

Construction of a Gaussian Process Regression Model of Formamide for Use in Molecular Simulations
por: Brown, Matthew L., et al.
Publicado: (2023)

Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks
por: Richter, Philipp, et al.
Publicado: (2015)

Gaussian Process Regression Tuned by Bayesian Optimization for Seawater Intrusion Prediction
por: Kopsiaftis, George, et al.
Publicado: (2019)

Localization Reliability Improvement Using Deep Gaussian Process Regression Model
por: Teng, Fei, et al.
Publicado: (2018)

Adaptive Bayesian credible bands in regression with a Gaussian process prior
por: Sniekers, Suzanne, et al.
Publicado: (2019)

Stiffness estimation of planar spiral spring based on Gaussian process regression
por: Liu, Jingjing, et al.
Publicado: (2022)

Gaussian process regression bootstrapping: exploring the effects of uncertainty in time course data
por: Kirk, Paul D. W., et al.
Publicado: (2009)

Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression
por: Salinero-Delgado, Matías, et al.
Publicado: (2021)

Comprehensive Modeling in Predicting Biodiesel Density Using Gaussian Process Regression Approach
por: Wang, Bingxian, et al.
Publicado: (2021)

Gaussian Process Regressions for Inverse Problems and Parameter Searches in Models of Ventricular Mechanics
por: Di Achille, Paolo, et al.
Publicado: (2018)

Wireless Indoor Localization Using Convolutional Neural Network and Gaussian Process Regression
por: Zhang, Guolong, et al.
Publicado: (2019)

A Gaussian process regression model to predict energy contents of corn for poultry
por: Baiz, Abbas Abdullah, et al.
Publicado: (2020)

Relative cooling power modeling of lanthanum manganites using Gaussian process regression
por: Zhang, Yun, et al.
Publicado: (2020)

An Extended Kalman Filter for Magnetic Field SLAM Using Gaussian Process Regression
por: Viset, Frida, et al.
Publicado: (2022)

A novel correlation Gaussian process regression-based extreme learning machine
por: Ye, Xuan, et al.
Publicado: (2023)

Validating the Use of Gaussian Process Regression for Adaptive Mapping of Residual Stress Fields
por: Fancher, Chris M., et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_7rs3n9mj1u0n9p036lan4li454