maui

Autoencoder toolkit

An autoencoder-based toolkit for multi-omics data analysis using Bayesian latent factor models and deep learning

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

GitHub

48 stars
15 watching
20 forks
Language: Jupyter Notebook
last commit: over 1 year ago
Linked from 1 awesome list

autoencoderbioinformaticscancer-genomicsdeep-learninglatent-factor-modelmulti-omics

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
trungnt13/sisua A software framework for semi-supervised generative Autoencoder models applied to single-cell data analysis. 18
datacanvasio/cooka An automated machine learning toolkit with visualization and feature engineering capabilities 40
pku-dair/mindware An efficient AutoML system that automates the machine learning lifecycle 52
zhangxiaoyu11/omivae An end-to-end deep learning model that extracts low-dimensional latent space and performs multi-class classification on multi-omics datasets. 31
zheng-yuwei/stacked_autoencoder This software enables the creation of deep learning networks with stacked auto-encoders and fine-tunes them using backpropagation for image classification tasks. 41
zudi-lin/pytorch_connectomics A deep learning framework for automatic and semi-automatic segmentation of 3D image stacks in connectomics 171
code-kern-ai/refinery A tool to help data scientists manage and annotate natural language data for training AI models 1,402
beastbyteai/falcon Automates machine learning model training using pre-set configurations and modular design. 159
chapmanb/bcbb A collection of reusable code for biological analysis and high-throughput sequencing 611
mop/bier This project implements a deep metric learning framework using an adversarial auxiliary loss to improve robustness. 39
albermax/innvestigate A toolbox to help understand neural networks' predictions by providing different analysis methods and a common interface. 1,265
thumnlab/autogl An autoML framework for machine learning on graphs, enabling researchers and developers to automate the process of building and training neural networks on graph data. 1,088
microsoft/archai Automates the search for optimal neural network configurations in deep learning applications 467
numaproj/numalogic A collection of machine learning models and tools for real-time time series data analytics and anomaly detection 167
hernanmd/biosmalltalk A library for bioinformatics using Smalltalk 17