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02/11/2023
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis
Often, deep network models are purely inductive during training and whil...
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09/01/2022
Zero-Shot Multi-Modal Artist-Controlled Retrieval and Exploration of 3D Object Sets
When creating 3D content, highly specialized skills are generally needed...
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06/15/2022
A Multifidelity Monte Carlo Method for Realistic Computational Budgets
A method for the multifidelity Monte Carlo (MFMC) estimation of statisti...
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04/17/2022
Energetically Consistent Model Reduction for Metriplectic Systems
The metriplectic formalism is useful for describing complete dynamical s...
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04/13/2022
Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20≤SNR<30
The accuracy of the estimated stellar atmospheric parameter decreases ev...
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12/02/2021
Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation
Due to the curse of dimensionality and the limitation on training data, ...
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10/21/2021
A hyper-reduced MAC scheme for the parametric Stokes and Navier-Stokes equations
The need for accelerating the repeated solving of certain parametrized s...
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10/18/2021
Nonlinear Reduced DNN Models for State Estimation
We propose in this paper a data driven state estimation scheme for gener...
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10/05/2021
A Comparison of Neural Network Architectures for Data-Driven Reduced-Order Modeling
The popularity of deep convolutional autoencoders (CAEs) has engendered ...
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08/11/2021
Verifiability of the Data-Driven Variational Multiscale Reduced Order Model
In this paper, we focus on the mathematical foundations of reduced order...
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05/27/2021
High-Order Multirate Explicit Time-Stepping Schemes for the Baroclinic-Barotropic Split Dynamics in Primitive Equations
In order to treat the multiple time scales of ocean dynamics in an effic...
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05/25/2021
An efficient iterative method for solving parameter-dependent and random diffusion problems
This paper develops and analyzes a general iterative framework for solvi...
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05/23/2021
Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver
Partial differential equations are often used to model various physical ...
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04/29/2021
Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations
A dimension reduction method based on the "Nonlinear Level set Learning"...
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03/15/2021
A FOM/ROM Hybrid Approach for Accelerating Numerical Simulations
The basis generation in reduced order modeling usually requires multiple...
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02/28/2021
Structure-Preserving Galerkin POD-DEIM Reduced-Order Modeling of Hamiltonian Systems
A structure preserving proper orthogonal decomposition reduce-order mode...
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01/19/2021
Unified Robust Boosting
Boosting is a popular machine learning algorithm in regression and class...
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12/16/2020
A ROM-accelerated parallel-in-time preconditioner for solving all-at-once systems from evolutionary PDEs
In this paper we propose to use model reduction techniques for speeding ...
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12/01/2020
Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey
Reduced order models (ROMs) are computational models whose dimension is ...
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10/06/2020
Unified Robust Estimation via the COCO
Robust estimation is concerned with how to provide reliable parameter es...
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05/31/2020
A Virtual Obstacle Course within Diverse Sensory Environments
We developed a novel assessment platform with untethered virtual reality...
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04/17/2020
POD-(H)DG Method for Incompressible Flow Simulations
We present a reduced order method (ROM) based on proper orthogonal decom...
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12/23/2019
MM for Penalized Estimation
Penalized estimation can conduct variable selection and parameter estima...
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02/08/2019
Virtual Environments for Rehabilitation of Postural Control Dysfunction
We developed a novel virtual reality [VR] platform with 3-dimensional so...
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12/01/2017