reproducible-research

#计算机科学#A Collection of Variational Autoencoders (VAE) in PyTorch.

#计算机科学#Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

A DSL for data-driven computational pipelines

#计算机科学#Collection of popular and reproducible image denoising works.

#计算机科学#FMA: A Dataset For Music Analysis

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

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

#计算机科学#☁ 🚀 📊 📈 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 dimens...

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

Presentation-Ready Data Summary and Analytic Result Tables

#计算机科学#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

#计算机科学#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.

#计算机科学#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

#计算机科学#Experiments for understanding disentanglement in VAE latent representations

A research tool for the Iterated Prisoner's Dilemma