Implementação de metodologias baseadas em redes neurais para a solução de equações diferenciais parciais.

Paper: Modeling water and nitrogen dynamics in unsaturated soils using physics and multi-physics informed neural networks.

Official implementation of Conflict-Free Inverse Gradients Method

Course HW Submissions for Advanced Topics in Scientific Machine Learning

Comparative analysis of computational modeling of acoustic wave propagation using neural network-based methods.

A repository to learn about Physics-informed Neural Networks!

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

Programmes Python et C++ de mon projet tuteuré de S6. (2024)

This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.

Improving hyperthermia treatment by controlling temperature distribution in both 1D and 2D domains and thermal energy applied to cutaneous and subcutaneous tissues, through Bio-Heat equation with Physics-Informed Neural Networks (PINNs).

PINNs/FDM for 1D/2D heat and burgers equations

A Python General-Purpose Implementation For Physics Informed Neural Networks

Fitting 2D curves or Multi-variable partial Differential Equations

Solve 2D Navier-Stokes Equation using Physics-Informed Network

Repository for the Deep Learning in Scientific Computing course offered in Spring 2022 at ETH Zürich: Deep learning project with the aim of studying the preliminary design of a thermal energy storage.

Global Adaptive Search for Physics-informed Neural Networks

Simple example of PINNs usage

Machine learning for state-to-state

C++ automatic differentiation library with no dependencies and arbitrary higher order derivatives, stand-alone, header only

This repository contains the source code for the paper: "PINNing Cerebral Blood Flow: Analysis of Perfusion MRI in Infants using Physics-Informed Neural Networks"