biromiro/feup-pfl-proj-1

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Created about 3 years ago
Updated almost 3 years ago

biromiro/feup-pfl-proj-1

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feup-lcom

🖱️Proposed Solution for the Computer Laboratory Project @FEUP

pinn-multivp

💨 This repository contains the source code and additional resources for the paper "Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models". The paper discusses the challenges of solar wind forecasting and the application of Physics-Informed Neural Networks (PiNNs) to improve prediction accuracy and computational efficiency.

Jupyter Notebook

feup-sope

Solution proposal for the Operating Systems course exercises

polimi-naml

Numerical Analysis for Machine Learning

Jupyter Notebook

feup-gulbenkian-qc-mt

⚡ Developed Code for the New Talents in Quantum Technologies Program of the Gulbenkian Foundation / Capstone Project @FEUP

Jupyter Notebook

feup-cpd-proj

feup-cgra

🐟 Proposed project solution for the Computer Graphics course @ FEUP

feup-pfl

Solution proposal for the Functional and Logical Programming course exercises

feup-edaa-dcel

Implementation of the Doubly Connected Edge List (DCEL) Data Structure and application on the Map Overlay Problem

feup-sope-proj1

Proposed project solution for the Operating Systems course @ FEUP

pi-multivp

💨 This repository consolidates the source code and experimental results for two innovative approaches developed as part of a master thesis on solar wind forecasting: Physics-Informed Neural Networks (PiNN) and Physics-Informed Neural Operators (PiNO).

pignn-multivp

💨 This repository contains the experiments with Physics-Informed Graph Neural Networks (PiGNNs) for Solar Wind Modelling to improve prediction accuracy and computational efficiency.

Jupyter Notebook

feup-iart-proj1

🤖 Proposed project solution for the Artificial Intelligence course @ FEUP

cs-ai-summer-school-challenge

🤖 CentraleSupelec Summer School on AI 2022 - Classify an email into eight classes based on the metadata extracted from the emails.

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pod-pinn

🌀 This repository contains the implementation of a physics-informed surrogate model leveraging Proper Orthogonal Decomposition (POD) and neural networks to solve the inviscid Burgers' equation efficiently.

Jupyter Notebook

pino-multivp

💨 This repository contains the source code and resources for the approach "Leveraging Physics-Informed Neural Operators as Solar Wind Forecasting Models". The paper discusses the challenges of solar wind forecasting and the application of Physics-Informed Neural Operators (PiNOs) to improve prediction accuracy and computational efficiency.

Jupyter Notebook