Machine learning for chemical reactions
M Meuwly - Chemical Reviews, 2021 - ACS Publications
Machine learning (ML) techniques applied to chemical reactions have a long history. The
present contribution discusses applications ranging from small molecule reaction dynamics …
present contribution discusses applications ranging from small molecule reaction dynamics …
State-of-the-art and comparative review of adaptive sampling methods for kriging
Metamodels aim to approximate characteristics of functions or systems from the knowledge
extracted on only a finite number of samples. In recent years kriging has emerged as a …
extracted on only a finite number of samples. In recent years kriging has emerged as a …
Multisystem Bayesian constraints on the transport coefficients of QCD matter
We study the properties of the strongly coupled quark-gluon plasma with a multistage model
of heavy-ion collisions that combines the TR ENTo initial condition ansatz, free-streaming …
of heavy-ion collisions that combines the TR ENTo initial condition ansatz, free-streaming …
A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design
Metamodeling is becoming a rather popular means to approximate the expensive
simulations in today's complex engineering design problems since accurate metamodels …
simulations in today's complex engineering design problems since accurate metamodels …
Paper recommender systems: a literature survey
In the last 16 years, more than 200 research articles were published about research-paper
recommender systems. We reviewed these articles and present some descriptive statistics in …
recommender systems. We reviewed these articles and present some descriptive statistics in …
A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses
Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-
order) aerodynamic models or flight testing are some of the fundamental but complex steps …
order) aerodynamic models or flight testing are some of the fundamental but complex steps …
An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach
Summary Continuously indexed Gaussian fields (GFs) are the most important ingredient in
spatial statistical modelling and geostatistics. The specification through the covariance …
spatial statistical modelling and geostatistics. The specification through the covariance …
Remarks on multi-output Gaussian process regression
Multi-output regression problems have extensively arisen in modern engineering
community. This article investigates the state-of-the-art multi-output Gaussian processes …
community. This article investigates the state-of-the-art multi-output Gaussian processes …
Regression and Kriging metamodels with their experimental designs in simulation: A review
JPC Kleijnen - European Journal of Operational Research, 2017 - Elsevier
This article reviews the design and analysis of simulation experiments. It focusses on
analysis via two types of metamodel (surrogate. emulator); namely, low-order polynomial …
analysis via two types of metamodel (surrogate. emulator); namely, low-order polynomial …
DiceKriging, DiceOptim: Two R packages for the analysis of computer experiments by kriging-based metamodeling and optimization
O Roustant, D Ginsbourger, Y Deville - Journal of statistical software, 2012 - jstatsoft.org
We present two recently released R packages, DiceKriging and DiceOptim, for the
approximation and the optimization of expensive-to-evaluate deterministic functions …
approximation and the optimization of expensive-to-evaluate deterministic functions …