Stars
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
A scalable SCENIC workflow for single-cell gene regulatory network analysis
Bayesian Data Analysis demos for Python
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders
DAGs with NO TEARS: Continuous Optimization for Structure Learning
An index of algorithms for learning causality with data
Realistic in silico generation and augmentation of single cell RNA-seq data using Generative Adversarial Neural Networks
PyTorch implementations of Generative Adversarial Networks.
BEELINE: evaluation of algorithms for gene regulatory network inference
Fast, flexible and easy to use probabilistic modelling in Python.
Some custom dataset examples for PyTorch
Build your neural network easy and fast, 莫烦Python中文教学
Deep probabilistic analysis of single-cell and spatial omics data
A deep learning-based tool for alignment and integration of single cell genomic data across multiple datasets, species, conditions, batches
Deep count autoencoder for denoising scRNA-seq data
Python package for dimension reduction of high-dimensional biological data.
Simple PyTorch Tutorials Zero to ALL!