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01/28/2023
MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics
Gradient-based meta-learning methods have primarily been applied to clas...
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01/11/2023
Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures
Molecular dynamics (MD) has served as a powerful tool for designing mate...
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12/29/2022
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation
Neural operators, which emerge as implicit solution operators of hidden ...
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11/27/2022
OBMeshfree: An optimization-based meshfree solver for nonlocal diffusion and peridynamics models
We present OBMeshfree, an Optimization-Based Meshfree solver for compact...
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06/04/2022
MetaNOR: A Meta-Learnt Nonlocal Operator Regression Approach for Metamaterial Modeling
We propose MetaNOR, a meta-learnt approach for transfer-learning operato...
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04/01/2022
A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues from Digital Image Correlation Measurements
We present a data-driven workflow to biological tissue modeling, which a...
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03/15/2022
Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling
Constitutive modeling based on continuum mechanics theory has been a cla...
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02/14/2022
A Meshfree Peridynamic Model for Brittle Fracture in Randomly Heterogeneous Materials
In this work we aim to develop a unified mathematical framework and a re...
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01/06/2022
Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network
Neural operators have recently become popular tools for designing soluti...
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01/05/2021
An asymptotically compatible treatment of traction loading in linearly elastic peridynamic fracture
Meshfree discretizations of state-based peridynamic models are attractiv...
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12/08/2020
Data-driven learning of nonlocal models: from high-fidelity simulations to constitutive laws
We show that machine learning can improve the accuracy of simulations of...
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05/17/2020
Data-driven learning of robust nonlocal physics from high-fidelity synthetic data
A key challenge to nonlocal models is the analytical complexity of deriv...
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12/13/2019
An Asymptotically Compatible Formulation for Local-to-Nonlocal Coupling Problems without Overlapping Regions
In this paper we design and analyze an explicit partitioned procedure fo...
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08/11/2019
