
DGM
 Referenced in 152 articles
[sw39282]
 deep learning algorithm for solving partial differential equations. Highdimensional PDEs have been a longstanding ... highdimensional HamiltonJacobiBellman PDE and Burgers’ equation. The deep learning algorithm approximates ... which can be viewed as a highdimensional space). We call the algorithm a “Deep...

hglasso
 Referenced in 11 articles
[sw11202]
 consider the problem of learning a highdimensional graphical model in which there ... order to learn a sparse graph in the highdimensional setting. However...

GPCOACH
 Referenced in 10 articles
[sw09137]
 based learning of COmpact and ACcurate fuzzy rulebased classification systems for Highdimensional problems ... Genetic Programmingbased method for the learning of COmpact and ACcurate fuzzy rule ... based classification systems for Highdimensional problems. GPCOACH learns disjunctive normal form rules (generated...

camel
 Referenced in 10 articles
[sw14318]
 implementation of a family of highdimensional calibrated machine learning tools, including (1) LAD, SQRT...

NICE
 Referenced in 14 articles
[sw29631]
 propose a deep learning framework for modeling complex highdimensional densities called Nonlinear Independent ... linear deterministic transformation of the data is learned that maps it to a latent space...

NeuralPDE.jl
 Referenced in 33 articles
[sw39548]
 partial differential equations using scientific machine learning (SciML) techniques such as physicsinformed neural networks ... neural stochastic differential equations to solve highdimensional PDEs at a greatly reduced cost...

Celer
 Referenced in 5 articles
[sw37123]
 inducing regularizations are ubiquitous in highdimensional machine learning, but solving the resulting optimization problems...

CHIME
 Referenced in 9 articles
[sw28514]
 highdimensional Gaussian mixtures with EM algorithm and its optimality. Unsupervised learning is an important ... learning with a wide range of applications. In this paper, we study clustering of high ... dimensional Gaussian mixtures and propose a procedure, called CHIME, that is based...

CORe50
 Referenced in 4 articles
[sw37988]
 Continuous Object Recognition. Continuous/Lifelong learning of highdimensional data streams is a challenging research problem ... recognition applications (e.g., robotic vision), where continuous learning is crucial, very few datasets and benchmarks...

FASTA
 Referenced in 13 articles
[sw37234]
 machine learning, signal and image processing, communications, and beyond. For highdimensional minimization problems involving...

bartMachine
 Referenced in 10 articles
[sw10962]
 package bartMachine: Machine learning with Bayesian additive regression trees. We present a new package ... handling both large sample sizes and highdimensional data...

GANomaly
 Referenced in 5 articles
[sw41240]
 adversarial network that jointly learns the generation of highdimensional image space and the inference ... latent vectors during training aids in learning the data distribution for the normal samples...

LWPR
 Referenced in 7 articles
[sw13543]
 LWPR), a supervised learning algorithm that is capable of handling highdimensional input data...

spectralGraphTopology
 Referenced in 1 article
[sw35465]
 data and hyperconnectivity, learning highdimensional structures such as graphs from data has become ... prominent task in machine learning and has found applications in many fields such as finance...

ZOOpt
 Referenced in 2 articles
[sw22396]
 optimization problems in machine learning, addressing highdimensional, noisy, and largescale problems. The toolbox ... tools in realworld machine learning tasks...

MetaGrad
 Referenced in 1 article
[sw40373]
 full covariance matrix and is applicable to learning tasks for which we can afford update ... versions provide speedups for highdimensional learning tasks with an update time that...

datamicroarray
 Referenced in 6 articles
[sw25719]
 load smallsample, highdimensional microarray data sets to assess machine learning algorithms and models...

BARTBMA
 Referenced in 5 articles
[sw23498]
 considered a Bayesian version of machine learning tree ensemble methods where the individual trees ... popular for highdimensional data is random forests, a machine learning algorithm which grows trees ... based algorithm which can deal with highdimensional data. We have found that BART...

BaRC
 Referenced in 3 articles
[sw40037]
 attractive approach to learn control policies for highdimensional systems, but its relatively poor sample ... amount of exploration required to obtain a learning signal from the initial state...

ASKIT
 Referenced in 11 articles
[sw17470]
 ASKIT: an efficient, parallel library for highdimensional kernel summations. Kernelbased methods ... powerful tool in a variety of machine learning and computational statistics methods. A key bottleneck...