Deep probabilistic analysis of single-cell and spatial omics data
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Updated
May 10, 2024 - Python
Deep probabilistic analysis of single-cell and spatial omics data
Variational Animal Motion Embedding - A tool for time series embedding and clustering
Variational Inference for Cell Type Evolution
Collection of operational time series ML models and tools
Unofficial Pytorch Implementation of the Nouveau Variational AutoEncoder (NVAE) paper.
PoseModel: An Open-Source Toolkit for Accurate and Robust Automated Behavioral Latent Embedding
Authors' PyTorch implementation of lossy image compression methods that are based on hierarchical VAEs
Manifold learning for single-cell single-nucleotide genetic variations
A GenAI app to generate hand-written characters
The Anonymous Synthesizer for Health Data
There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.
Learn Generative AI with PyTorch (Manning Publications, 2024)
MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations
A study on the loss of data variability in (generative) variational autoencoders, with a focus on architectural modifications to mitigate the effect.
Experiments with fuzzy layers and neural nerworks
Variational Autoencoder that is trained to generate or reconstruct audio of spoken digits from 0 to 9
Federated learning with PyTorch (federated averaging and consensus optimization): with 'reduced' bandwidth
"Deep Generative Modeling": Introductory Examples
Target-aware Variational Auto-encoders for Ligand Generation with Multimodal Protein Representation Learning
Explore, compare and develop autoencoder models with a back-end agnostic framework
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