🦉 Data Versioning and ML Experiments

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

Accelerated deep learning R&D

This is the development home of the workflow management system Snakemake. For general information, see

A toolkit for reproducible reinforcement learning research.

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

☁️ 🚀 📊 📈 Evaluating state of the art in AI

The collaboration workspace for Machine Learning

A comparison between some VPS providers. It uses Ansible to perform a series of automated benchmark tests over the VPS servers that you specify. It allows the reproducibility of those tests by anyone that wanted to compare these results to their own. All the tests results are available in order to provide independence and transparency.

An R-focused pipeline toolkit for reproducibility and high-performance computing

Dev environments for numerous languages based on Nix flakes [maintainer=@lucperkins]

Presentation-Ready Data Summary and Analytic Result Tables

Simplified nix packaging for various programming language ecosystems [maintainer=@DavHau]

High-fidelity performance metrics for generative models in PyTorch

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Function-oriented Make-like declarative workflows for R

Create highly reproducible python environments

Workflow Description Language - Specification and Implementations