joaomarcoscsilva
Computer Science student at USP, interested in Self-Supervised Learning, Information Theory and Probabilistic Machine Learning
Universidade de São PauloMarília, São Paulo
Pinned Repositories
Adversarially-Constrained-Autoencoder-Interpolation
Replication of the paper by Beckham et al. applied to a pokemon dataset.
Babysitter
cassava
Conditional-DCGAN
Implements a conditional DCGAN to generate specific characters from the MNIST dataset.
Generative-Adversarial-Network
An implementation of the paper by Ian Goodfellow applied to the MNIST dataset.
issues-covid-image-diagnosis
Code for the paper "Detecting and mitigating issues in image-based COVID-19 diagnosis", https://proceedings.mlr.press/v184/silva22a.html
mixture-of-experts
A replication of the paper "Adaptive Mixtures of Local Experts" applied to the CIFAR-10 image classification dataset.
pesquisa-eleitoral-interpretador
Aplicativo Python que interpreta os dados coletados na pesquisa
soundscape
Code for semi-supervised soundscape ecology with JAX and Tensorflow
joaomarcoscsilva's Repositories
joaomarcoscsilva/mixture-of-experts
A replication of the paper "Adaptive Mixtures of Local Experts" applied to the CIFAR-10 image classification dataset.
joaomarcoscsilva/Generative-Adversarial-Network
An implementation of the paper by Ian Goodfellow applied to the MNIST dataset.
joaomarcoscsilva/issues-covid-image-diagnosis
Code for the paper "Detecting and mitigating issues in image-based COVID-19 diagnosis", https://proceedings.mlr.press/v184/silva22a.html
joaomarcoscsilva/pesquisa-eleitoral-interpretador
Aplicativo Python que interpreta os dados coletados na pesquisa
joaomarcoscsilva/Adversarially-Constrained-Autoencoder-Interpolation
Replication of the paper by Beckham et al. applied to a pokemon dataset.
joaomarcoscsilva/Babysitter
joaomarcoscsilva/cassava
joaomarcoscsilva/Conditional-DCGAN
Implements a conditional DCGAN to generate specific characters from the MNIST dataset.
joaomarcoscsilva/Conditional-Generative-Adversarial-Network
Implements the paper by Mehdi Mirza and applies it to the MNIST dataset.
joaomarcoscsilva/soundscape
Code for semi-supervised soundscape ecology with JAX and Tensorflow
joaomarcoscsilva/Conicas
joaomarcoscsilva/Coronavirus-Graph
Plots graphs containing updated information about the coronavirus spread internationally
joaomarcoscsilva/Deep-Convolutional-Generative-Adversarial-Network
Implements the paper and applies it to the MNIST dataset
joaomarcoscsilva/Fonte-3-12V
Circuito de uma fonte de 100mA de 3 a 12 volts
joaomarcoscsilva/hackaton-cohere
joaomarcoscsilva/jmcsilva
joaomarcoscsilva/joaomarcoscsilva.github.io
A beautiful, simple, clean, and responsive Jekyll theme for academics
joaomarcoscsilva/keras-cv
Industry-strength Computer Vision workflows with Keras
joaomarcoscsilva/meta-learning
Replicates some meta-learning papers
joaomarcoscsilva/MuseScore
MuseScore is an open source and free music notation software. For support, contribution, bug reports, visit MuseScore.org. Fork and make pull requests!
joaomarcoscsilva/oryx
Oryx is a library for probabilistic programming and deep learning built on top of Jax.
joaomarcoscsilva/PAS-Classificacao-Ordenada
joaomarcoscsilva/pendencias-android
Android app that downloads, formats and displays information about school activities on Google Drive from pendencias-server.
joaomarcoscsilva/pesquisa-eleitoral
An android app that implements a form for research about the 2018 brazilian presidential election and then uploads the results to a kinto server.
joaomarcoscsilva/pesquisa-eleitoral-server
O servidor kinto da pesquisa eleitoral
joaomarcoscsilva/Pokemon-Interpolator
An autoencoder capable of mixing two images of pokemon into a new, semantically meaningful image (dataset and idea by youtuber Jabrils)
joaomarcoscsilva/probability
Probabilistic reasoning and statistical analysis in TensorFlow
joaomarcoscsilva/reddit_classifier
joaomarcoscsilva/zetaglest-source
ZetaGlest is a fork of MegaGlest, a network multi-player cross-platform 3D real-time strategy (RTS) game, where you create armies of units and battle different factions.
joaomarcoscsilva/zetaglest.github.io
ZetaGlest web site repo