Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.

Deep learning on histopathology images.

SEQUOIA: Digital profiling of cancer transcriptomes with grouped vision attention

This repository contains data and other materials related to the DeepPT manuscript

Exemplar Guided Deep Neural Network for Spatial Transcriptomics Analysis of Gene Expression Prediction

Reproducing results from Multigrate paper

A Collection of Variational Autoencoders (VAE) in PyTorch.

Graph-linked unified embedding for single-cell multi-omics data integration

Variational autoencoder for single-cell integration and transfer learning.

Reproducing all analyses and figures for the ASAP-seq paper

This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.

Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering

Implementation of Generating Diverse High-Fidelity Images with VQ-VAE-2 in PyTorch

Experiments for understanding disentanglement in VAE latent representations

Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation 🌟

Vector Quantized VAEs - PyTorch Implementation

Roundtrip: density estimation with deep generative neural networks

collections for advanced, novel multi-view clustering methods(papers , codes and datasets)

Continuously Updating ...... Please star me!

这是一个YoloV4-tiny-pytorch的源码，可以用于训练自己的模型。

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)

Proximal optimization in pure python

Training Neural Networks Without Gradients: A ADMM Approach