adsmendesdaniel

adsmendesdaniel's Stars

• fchollet/deep-learning-with-python-notebooks

  Jupyter notebooks for the code samples of the book "Deep Learning with Python"

  Language:Jupyter Notebook18.2k6471848.5k

• Blealtan/efficient-kan

  An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

  Language:Python3.8k3337339

• lululxvi/deepxde

  A library for scientific machine learning and physics-informed learning

  Language:Python2.6k56767733

• spectralDNS/shenfun

  High performance computational platform in Python for the spectral Galerkin method

  Language:Python196147042

• idies/pyJHTDB

  Python wrapper for the Johns Hopkins turbulence database library

  Language:C96213847

• OpenChrom/openchrom

  Visualization and Analysis of mass spectrometric and chromatographic data.

  Language:Java82630924

• PredictiveIntelligenceLab/PINNsNTK

  Language:Jupyter Notebook8212531

• vsantjr/IDeepS

  Project IDeepS: Image and data classification via Deep neural networks for multiple domainS

  Language:Python10200

• danielhalvorsen/Project_Turbulence_Modelling

  Repository for project codes related to turbulence modelling.

  Language:Python85

• hektor-monteiro/python-notebooks

  Curso de computação científica com uso de Python

  Language:Jupyter Notebook77

• bfalck/indra-tools

  Code repository for the Indra simulations

  Language:Jupyter Notebook5101

• tkorting/remote-sensing-images

  Images obtained by remote sensing satellites, for testing with Google colab

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• ai4luc/AI4LUC

  Language:Python4101

• rsautter/GPA

  Gradient Pattern Analysis in Cython

  Language:Jupyter Notebook4102

• monanadmin/MONAN-Model

  MONAN - Model for Ocean-laNd-Atmosphere PredictioN

  Language:Fortran38224

• rsautter/Chi-Space

  Multifractal and Spectral Entropy space

  Language:Python3100

• duducosmos/pycosmicstar

  The Cosmic Star Formation Rate Model

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• Fari97/Deep-Backward-Heat-Conduction-Problem

  Language:Python21

• adsmendesdaniel/adsmendesdaniel

  1200

• adsmendesdaniel/adsmendesdaniel.github.io

  :iphone: App marketing template for Jekyll

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• adsmendesdaniel/adsmendesdaniel.github.io_OLD

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• adsmendesdaniel/Forecasting-the-COVID-19-behavior-with-Differential-Evolution-and-a-combination-of-gaussians-model

  Analysis of time series datasets of recorded cases and deaths from COVID-19 and cases and deaths from SARS (severe acute respiratory syndrome) using Differential Evolution and the combination of Gaussian distribution waves to forecast the behavior of the second wave of COVID-19 in Brazil.

  Language:Jupyter Notebook1200

• adsmendesdaniel/Forecasting-the-COVID-19-behavior-with-Differential-Evolution-and-a-Maxwell-Boltzmann-like-model

  Analysis of time series datasets of recorded cases and deaths from COVID-19 and recorded cases and deaths from SARS (severe acute respiratory syndrome) in Brazil using Differential Evolution and a combination model of "Maxwell-Boltzmann-like" distributions to forecast the behavior of the first and second wave of COVID-19 in Brazil.

  Language:Jupyter Notebook1201

• efurlanm/421

  CAP 421 Deep Learning

  Language:Jupyter Notebook1100

• efurlanm/msc22

  My MSc Thesis

  Language:Jupyter Notebook1

• frequencia-unifei/frequencia-unifei.github.io

  Agency Theme for Jekyll

  Language:JavaScript10

• Gremling-Machine-Learning-Study-Group/Estimativa-de-mortes-por-COVID-19-subnotificadas-no-Brasil---D051---HACKCOVID-19

  Parte 1 do desafio "IA E CIÊNCIA DE DADOS PARA APOIO A DECISÃO CLÍNICA" da Hackathon 'Hackcovid19' do Centro Brasileiro de Pesquisas Físicas, onde utilizamos conceitos simples de estatística, probabilidade e 'datascience' para tentar estimar a quantidade de casos de mortes por Síndrome Respiratória Aguda que foram causadas por COVID-19, porém não foram reportadas como tal.

  Language:Jupyter Notebook1200

• Gremling-Machine-Learning-Study-Group/Pre-processamento-em-Espectrometria-de-Massa-para-Modelos-de-Aprendizado-de-Maquina

  1200

• rsautter/CyMorph-2DX

  An opensource package for astronomical photometry

  Language:Jupyter Notebook1200

• rsautter/GPA_Tutorial

  Language:Jupyter Notebook10