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07/05/2022
opPINN: Physics-Informed Neural Network with operator learning to approximate solutions to the Fokker-Planck-Landau equation
We propose a hybrid framework opPINN: physics-informed neural network (P...
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04/29/2022
AL-PINNs: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks
Physics-Informed Neural Networks (PINNs) has become a prominent applicat...
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01/28/2022
Pseudo-Differential Integral Operator for Learning Solution Operators of Partial Differential Equations
Learning mapping between two function spaces has attracted considerable ...
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11/09/2021
Solving PDE-constrained Control Problems using Operator Learning
The modeling and control of complex physical dynamics are essential in r...
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09/30/2021
The Deep Minimizing Movement Scheme
Solutions of certain partial differential equations (PDEs) are often rep...
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09/18/2021
Development of patients triage algorithm from nationwide COVID-19 registry data based on machine learning
Prompt severity assessment model of confirmed patients who were infected...
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06/23/2021
Lagrangian dual framework for conservative neural network solutions of kinetic equations
In this paper, we propose a novel conservative formulation for solving k...
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01/22/2021
Prior Preference Learning from Experts:Designing a Reward with Active Inference
Active inference may be defined as Bayesian modeling of a brain with a b...
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01/22/2021
Sobolev Training for the Neural Network Solutions of PDEs
Approximating the numerical solutions of Partial Differential Equations ...
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01/21/2021
Traveling Wave Solutions of Partial Differential Equations via Neural Networks
This paper focuses on how to approximate traveling wave solutions for va...
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09/28/2020
The model reduction of the Vlasov-Poisson-Fokker-Planck system to the Poisson-Nernst-Planck system via the Deep Neural Network Approach
The model reduction of a mesoscopic kinetic dynamics to a macroscopic co...
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08/28/2020
Posting Bot Detection on Blockchain-based Social Media Platform using Machine Learning Techniques
Steemit is a blockchain-based social media platform, where authors can g...
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11/22/2019
Trend to Equilibrium for the Kinetic Fokker-Planck Equation via the Neural Network Approach
The issue of the relaxation to equilibrium has been at the core of the k...
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11/07/2019
Option Compatible Reward Inverse Reinforcement Learning
Reinforcement learning with complex tasks is a challenging problem. Ofte...
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09/06/2019
NEAR: Neighborhood Edge AggregatoR for Graph Classification
Learning graph-structured data with graph neural networks (GNNs) has bee...
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07/27/2019
Deep Neural Network Approach to Forward-Inverse Problems
In this paper, we construct approximated solutions of Differential Equat...
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10/05/2018
