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

FMA: A Dataset For Music Analysis

Collection of popular and reproducible image denoising works.

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

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

High-fidelity performance metrics for generative models in PyTorch

Function-oriented Make-like declarative workflows for R

PyCIL: A Python Toolbox for Class-Incremental Learning

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.

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