Deep Ritz Method for solving PDE
DeepONet & FNO (with practical extensions)
Koopman theory implemented using deep learning
Use Fourier transform to learn operators in differential equations.
gPINN: Gradient-enhanced physics-informed neural networks
Official implementation of *A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs*
Tutorials on math epidemiology and epidemiology informed deep learning methods
MIONet: Learning multiple-input operators via tensor product
Radiative transfer with advanced machine learning methods
A machine learning boosted parallel-in-time differential equation solver framework.
This is the code and data for the IEEE TPEL paper "Parameter Estimation of Power Electronic Converters with Physics-informed Machine Learning"
A project providing a framework to solve many kinds of differential equations using neural networks.
Non-adaptive and residual-based adaptive sampling for PINNs
NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
Implementation of Hinton's forward-forward (FF) algorithm - an alternative to back-propagation
SBINN: Systems-biology informed neural network
Inverse and forward scattering problems via PINNs
An open access book on scientific visualization using python and matplotlib
Data loaders and abstractions for text and NLP
Code Repository for The Kaggle Book, Published by Packt Publishing
WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)