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

49 stars
15 watching
21 forks
Language: Jupyter Notebook
last commit: about 3 years ago
Linked from 1 awesome list

autoencoderbioinformaticscancer-genomicsdeep-learninglatent-factor-modelmulti-omics

Backlinks from these awesome lists:

Related projects:

RepositoryDescriptionStars
trungnt13/sisuaA software framework for semi-supervised generative Autoencoder models applied to single-cell data analysis.18
datacanvasio/cookaAn automated machine learning toolkit with visualization and feature engineering capabilities40
pku-dair/mindwareAn efficient AutoML system that automates the machine learning lifecycle53
zhangxiaoyu11/omivaeThis project provides an end-to-end deep learning model for low dimensional latent space extraction and multi-class classification on multi-omics datasets.31
zheng-yuwei/stacked_autoencoderThis 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_connectomicsA deep learning framework for automatic and semi-automatic segmentation of 3D image stacks in connectomics172
code-kern-ai/refineryA tool to help data scientists manage and annotate natural language data for training AI models1,405
beastbyteai/falconAutomates machine learning model training using pre-set configurations and modular design.159
chapmanb/bcbbA collection of reusable code for biological analysis and high-throughput sequencing612
mop/bierThis project implements a deep metric learning framework using an adversarial auxiliary loss to improve robustness.39
albermax/innvestigateA toolbox to help understand neural networks' predictions by providing different analysis methods and a common interface.1,271
thumnlab/autoglAn autoML framework for machine learning on graphs, enabling researchers and developers to automate the process of building and training neural networks on graph data.1,094
microsoft/archaiAutomates the search for optimal neural network configurations in deep learning applications468
numaproj/numalogicA collection of machine learning models and tools for real-time time series data analytics and anomaly detection168
hernanmd/biosmalltalkA library for bioinformatics using Smalltalk17