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Search results for deep learning physics informed neural networks
deep-learning
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physics-informed-neural-networks
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17 search results found
Neurodiffeq
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576
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
Pdebench
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522
PDEBench: An Extensive Benchmark for Scientific Machine Learning
Pina
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195
Physics-Informed Neural networks for Advanced modeling
Heat Pinn
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53
A Physics-Informed Neural Network to solve 2D steady-state heat equation.
Deep_learning_for_dynamical_systems
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31
Gpt Pinn
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22
Generative Pre-Trained Physics-Informed Neural Networks Implementation
Das
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20
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations
Ms Hpc Ai Gpu
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19
resources pour le cours d'introduction à la programmation des GPUs du mastère spécialisé HPC-AI
Pararealml
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19
A machine learning boosted parallel-in-time differential equation solver framework.
Lpinns
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18
To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to the direction of travel of information in convection-diffusion equations, i.e., method of characteristic; The repository includes a pytorch implementation of PINN and proposed LPINN with periodic boundary conditions
Burger Pinn
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17
A Physics-Informed Neural Network for solving Burgers' equation.
Mathepideeplearning
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15
Awesome-spatial-temporal-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included. Keep updating.
Model Collection
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11
This project contains a collection of deep learning models developed by the AI4Sim team with various partners. This is is structured on the basis of use-cases providing canonical PyTorch Lightning pipelines allowing to train neural network models that are able to surrogate various physical processes.
Adaptive Optimization Of Pinn
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9
Optimizing Physics-Informed NN using Multi-task Likelihood Loss Balance Algorithm and Adaptive Activation Function Algorithm
Deepsysid
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9
System identification toolkit for multistep prediction using deep learning and hybrid methods.
Pinnlearning
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7
Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN
Bubblenet
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6
A physics-informed deep learning architecture for inferring bubble dynamics
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1-17 of 17 search results
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