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08/09/2023
Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators
We address the challenge of sound propagation simulations in 3D virtual ...
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04/15/2023
Learning in latent spaces improves the predictive accuracy of deep neural operators
Operator regression provides a powerful means of constructing discretiza...
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03/19/2023
LNO: Laplace Neural Operator for Solving Differential Equations
We introduce the Laplace neural operator (LNO), which leverages the Lapl...
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03/03/2023
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks
Deep neural networks are an attractive alternative for simulating comple...
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02/23/2023
Learning stiff chemical kinetics using extended deep neural operators
We utilize neural operators to learn the solution propagator for the cha...
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10/31/2022
On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations
The discovery of fast numerical solvers prompted a clear and rapid shift...
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07/08/2022
Physics-Informed Deep Neural Operator Networks
Standard neural networks can approximate general nonlinear operators, re...
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07/03/2022
Variational energy based XPINNs for phase field analysis in brittle fracture
Modeling fracture is computationally expensive even in computational sim...
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05/08/2022
Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms
Thoracic aortic aneurysm (TAA) is a localized dilatation of the aorta re...
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04/20/2022
Deep transfer learning for partial differential equations under conditional shift with DeepONet
Traditional machine learning algorithms are designed to learn in isolati...
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04/11/2022
Learning two-phase microstructure evolution using neural operators and autoencoder architectures
Phase-field modeling is an effective mesoscale method for capturing the ...
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03/09/2022
On the influence of over-parameterization in manifold based surrogates and deep neural operators
Constructing accurate and generalizable approximators for complex physic...
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11/20/2021
A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation
The phase-field fracture free-energy functional is non-convex with respe...
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08/16/2021
A physics-informed variational DeepONet for predicting the crack path in brittle materials
Failure trajectories, identifying the probable failure zones, and damage...
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08/27/2019
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications
Partial Differential Equations (PDE) are fundamental to model different ...
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07/04/2019
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture
We present a new physics informed neural network (PINN) algorithm for so...
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04/25/2019