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2trains

Training a ResNet18 on CIFAR10 with PyTorch and Keras

addons

Useful extra functionality for TensorFlow 2.0 maintained by SIG-addons

adler

General python utilities

ballon-dor

Looking at ballon d'or data to draw ccl about the best players of all time

benchmark_lasso

Benchopt benchmark for Lasso

benchmark_ot

Benchmark for Optimal transport libraries

benchopt

Making your benchmark of optimization algorithms simple and open

client

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

communication_materials

Resources for communication on Benchopt

coremltools

Converter tools for Core ML.

dask-jobqueue

Deploy Dask on job schedulers like PBS, SLURM, and SGE

deep-mri-reconstruction

Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction: Implementation & Demo

deep_equilibrium_inverse

Code related to the paper "Deep Equilibrium Architectures for Inverse Problems in Imaging"

deq

[NeurIPS'19] Deep Equilibrium Models

deq-flow

[CVPR 2022] Deep Equilibrium Optical Flow Estimation

diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

dncnn

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)

elder

fastmri

A large-scale dataset of both raw MRI measurements and clinical MRI images

fastmri-reproducible-benchmark

Try several methods for MRI reconstruction on the fastmri dataset. Home to the XPDNet, runner-up of the 2020 fastMRI challenge.

flax

Flax is a neural network library for JAX that is designed for flexibility.

git-tuto

A very sparse repo to practice the basics of git and GitHub flow in open source

glucose-challenge

Technical challenge

gml-project

Project for Graphs in machine learning class : correlation clustering

grappa

A repository to experiment on GRAPPA, with a TF backend. It also features some experiments on deep versions of GRAPPA

hoag

Code for the bi-level experiments of the ICLR 2022 paper "SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models" (on branch shine)

howtotrainyourmamlpytorch

The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.

hydra

Hydra is a framework for elegantly configuring complex applications

hypertorch

imaml_dev

Repo to accompany paper on Meta Learning with Implicit Gradients (NeurIPS 2019)