MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations
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Updated
Oct 28, 2024 - Jupyter Notebook
MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations
Disentangled Variational Auto-Encoder in TensorFlow / Keras (Beta-VAE)
Implementations of autoencoder, generative adversarial networks, variational autoencoder and adversarial variational autoencoder
TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)
Deep Probabilistic Programming Examples in Pytorch using pyro
Joint variational Autoencoders for Multimodal Imputation and Embedding (JAMIE)
probabilistic graphical model collections
Disentangling the latent space of a VAE.
Code for Adversarial Approximate Inference for Speech to Laryngograph Conversion
Some basic implementations of Variational Autoencoders in pytorch
Efficient C implementation of Quantum Analytic Descent
[Pytorch] Minimal implementation of a Variational Autoencoder (VAE) with Categorical Latent variables inspired from "Categorical Reparameterization with Gumbel-Softmax".
automatic/analytical differentiation benchmark
Anomaly detection in time series
Discrete Variational Autoencoder in PyTorch
Mixture of Bayes PCA | Variational Inference
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