Essays about: "Physics-Informed Deep Learning"
Found 3 essays containing the words Physics-Informed Deep Learning.
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1. Solving Partial Differential Equations With Neural Networks
University essay from Uppsala universitet/Matematiska institutionenAbstract : In this thesis three different approaches for solving partial differential equa-tions with neural networks will be explored; namely Physics-Informed NeuralNetworks, Fourier Neural Operators and the Deep Ritz method. Physics-Informed Neural Networks and the Deep Ritz Method are unsupervised machine learning methods, while the Fourier Neural Operator is a supervised method. READ MORE
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2. A Physics-Informed Deep Learning Framework for Solving Inverse Problems in Epidemiology
University essay from KTH/Optimeringslära och systemteoriAbstract : This thesis develops and evaluates a physics-informed neural network (PINN) modelling framework for solving inverse problems in epidemiology. The PINN works by modifying the standard mean squared error loss function of the neural network, by adding a term penalizing deviations from a given compartmental model's system of ordinary differential equations. READ MORE
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3. Physics-Informed Deep Learning for System Identification of Autonomous Underwater Vehicles : A Lagrangian Neural Network Approach
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this thesis, we explore Lagrangian Neural Networks (LNNs) for system identification of Autonomous Underwater Vehicles (AUVs) with 6 degrees of freedom. One of the main challenges of AUVs is that they have limited wireless communication and navigation under water. READ MORE
