🦉 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.
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
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.
☁️ 🚀 📊 📈 Evaluating state of the art in AI
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
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.
The open‑source AI Agents Governance & Orchestration framework: write the rules declaratively, Bernstein enforces them and produces the verifiable, replayable record. Free, Apache-2.0. https://bernstein.run
High-fidelity performance metrics for generative models in PyTorch
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
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.
Create highly reproducible python environments
Prepare Raspberry Pi 3, 4 & 5 configurations using a virtual machine.
Generic template to bootstrap your PyTorch project.
[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.
README-first research reproduction skills with bounded execution, auditable evidence, and byte-preserving README annotations.
Create powerful Hydra applications without the yaml files and boilerplate code.
To associate your repository with the reproducibility topic, visit your repo's landing page and select "manage topics."