kasparmartens/shared-private-multimodalVAE

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Created 11 months ago
Updated 11 months ago

kasparmartens/shared-private-multimodalVAE

kasparmartens

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Code for our paper "Disentangling shared and private latent factors in multimodal Variational Autoencoders"

NeuralProcesses

Neural Processes implementation for 1D regression

BasisVAE

PyTorch implementation of BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders

c-GPLVM

PyTorch implementation of the Covariate-GPLVM

NeuralDecomposition

PyTorch implementation of the paper "Neural Decomposition: Functional ANOVA with Variational Autoencoders"

Jupyter Notebook

NUTS

HMC No-U-Turn sampler (NUTS) implementation in R

mixtureModels

MCMC for Dirichlet Process mixture models

website

y10k-prediction

Code for our paper: Predicting quantitative traits from genome and phenome with near perfect accuracy

Jupyter Notebook

rarity

Implementarion of Rarity: Discovering rare cell populations from single-cell imaging data

ensembleFHMM

R package for ensemble MCMC for Factorial Hidden Markov Models