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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
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.
Sionna: An Open-Source Library for Research on Communication Systems
PyCIL: A Python Toolbox for Class-Incremental Learning
Scientific reports/literate programming for Julia
Experiments for understanding disentanglement in VAE latent representations
A research tool for the Iterated Prisoner's Dilemma
GPU-Jupyter: Your GPU-accelerated JupyterLab with a rich data science toolstack, TensorFlow and PyTorch for your reproducible deep learning experiments.