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cdedonno

Github homepage

comp-neuro

Code and notebooks for Computational Neuroscience class at TUM

convage

Convolutional Neural Network for prediction of future appearances on human faces.

cpa

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.

deep-face-saliency

gitignore

A collection of useful .gitignore templates

lish-moa

Kaggle competition MoA prediction

scgen

Single cell perturbation prediction

variational-autoencoder-pytorch

Variational Autoencoder implemented with PyTorch, Trained over CelebA Dataset