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D

Dimitris G. Giovanis

Johns Hopkins University

H指数:17

被引数:1,226

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Enabling probabilistic learning on manifolds through double diffusion maps

通过双扩散映射实现流形上的概率学习

Journal of Computational Physics

IF3.8

2026-01-090

PRE

Generative learning for slow manifolds and bifurcation diagrams

生成学习在慢流形和分岔图中的应用

Computers & Chemical Engineering

IF3.9

2025-12-300

PRE

Neural operators for stochastic modeling of nonlinear structural system response to natural hazards

神经网络算子用于非线性结构系统对自然灾害响应的随机建模

Engineering Structures

IF6.4

2025-09-250

PRE

UQpy Version 4.2: Uncertainty quantification with Python

UQpy版本4.2：基于Python的不确定性量化

IF2.4

2025-09-010

OAAI

Generative learning of densities on manifolds

流形上的密度生成学习

Computer Methods in Applied Mechanics and Engineering

IF7.3

2025-07-300

PRE

Implementing NLP in industrial process modeling: Addressing categorical variables

在工业过程建模中实施NLP：处理分类变量

COMPUTERS & CHEMICAL ENGINEERING

IF3.9

2025-05-150

OAAI

Integrating supervised and unsupervised learning approaches to unveil critical process inputs

COMPUTERS & CHEMICAL ENGINEERING

IF3.9

2025-01-011

OAAI

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

BULLETIN OF EARTHQUAKE ENGINEERING

IF4.1

2024-12-110

PRE

Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty

JOURNAL OF COMPUTATIONAL PHYSICS

IF3.8

2024-12-010

PRE

Discovering deposition process regimes: Leveraging unsupervised learning for process insights, surrogate modeling, and sensitivity analysis

CHEMICAL ENGINEERING JOURNAL ADVANCES

IF7.1

2024-11-010

OAAI

Revealing the hidden structure of disordered materials by parameterizing their local structural manifold

NATURE COMMUNICATIONS

IF15.7

2024-05-240

OAAI

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems

黑盒问题高维不确定性量化的无监督学习方法综述

JOURNAL OF COMPUTATIONAL PHYSICS

IF3.8

2022-09-0124

OAAI

Data-driven uncertainty quantification in computational human head models

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

IF7.3

2022-08-0111

OAAI

Imprecise subset simulation

PROBABILISTIC ENGINEERING MECHANICS

IF3.5

2022-07-014

OAAI

GRASSMANNIAN DIFFUSION MAPS-BASED DIMENSION REDUCTION AND CLASSIFICATION FOR HIGH-DIMENSIONAL DATA

基于GRASSMANNIAN扩散映射的高维数据降维与分类

SIAM JOURNAL ON SCIENTIFIC COMPUTING

IF2.6

2022-03-159

OA

Subset simulation for problems with strongly non-Gaussian, highly anisotropic, and degenerate distributions

COMPUTERS & STRUCTURES

IF4.8

2021-03-0120

PREAI

UQpy: A general purpose Python package and development environment for uncertainty quantification

nature computational science

IF3.7

2020-11-0152

OAAI

Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold

在Grassmann流形上使用高斯过程回归的高维模型的数据驱动代理

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

IF7.3

2020-10-0141

OAAI

A spectral stochastic formulation for nonlinear framed structures

PROBABILISTIC ENGINEERING MECHANICS

IF3.5

2019-01-015

PREAI

A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites

COMPUTATIONAL MECHANICS

IF3.8

2018-10-11139

PREAI