franciscojferrari's Stars
adam-p/markdown-here
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
iamadamdev/bypass-paywalls-chrome
Bypass Paywalls web browser extension for Chrome and Firefox.
Lightning-AI/pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
arendst/Tasmota
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
fengyuanchen/cropperjs
JavaScript image cropper.
optuna/optuna
A hyperparameter optimization framework
ashleve/lightning-hydra-template
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
Harry24k/adversarial-attacks-pytorch
PyTorch implementation of adversarial attacks [torchattacks]
giventofly/pixelit
Create pixel art from an image
BorealisAI/advertorch
A Toolbox for Adversarial Robustness Research
iot-salzburg/gpu-jupyter
GPU-Jupyter: Leverage the flexibility of Jupyterlab through the power of your NVIDIA GPU to run your code from Tensorflow and Pytorch in collaborative notebooks on the GPU.
karolzak/ipyplot
IPyPlot is a small python package offering fast and efficient plotting of images inside Python Notebooks. It's using IPython with HTML for faster, richer and more interactive way of displaying big numbers of images.
MadryLab/backgrounds_challenge
mtorchiano/effsize
Effsize - a package for efficient effect size computation
ftramer/MultiRobustness
Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
liuchen11/AdversaryLossLandscape
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]
locuslab/robust_union
[ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
decisionstats/python_for_datascience
Python for Data Science
pralab/Fast-Minimum-Norm-FMN-Attack
Foolbox implementation for NeurIPS 2021 Paper: "Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints".
facebookresearch/AdversarialAndDimensionality
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
ieeeuoft/traintrackr