reproducible-research

A Collection of Variational Autoencoders (VAE) in PyTorch.

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

A DSL for data-driven computational pipelines

Collection of popular and reproducible image denoising works.

FMA: A Dataset For Music Analysis

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

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

☁ 🚀 📊 📈 Evaluating state of the art in AI

Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.

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

Presentation-Ready Data Summary and Analytic Result Tables

High-fidelity performance metrics for generative models in PyTorch

Sionna: An Open-Source Library for Research on Communication Systems

Function-oriented Make-like declarative workflows for R

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.

PyCIL: A Python Toolbox for Class-Incremental Learning

Code to accompany our paper Chen and Zimmermann (2020), "Open source cross-sectional asset pricing"

Scientific reports/literate programming for Julia

Experiments for understanding disentanglement in VAE latent representations

A research tool for the Iterated Prisoner's Dilemma