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@XuegongLab

Beijing, China

MinshengHao's repositories

STEM

A Method for Mapping Single-cell and Spatial Transcriptomics Data with Transfer Learning

Language:Jupyter NotebookGPL-3.0600

somde

Algorithm for finding gene spatial pattern based on Gaussian process accelerated by SOM

Language:Jupyter NotebookMIT5 2 3

Entropy

just a idea./for ios app

Language:Python2 10

QtDish

QtDish, the first cross-platform application

Language:C++100

serverEntropy

work

Language:Python1 20

boston_housing

Udacity 机器学习工程师项目1

Language:HTML010

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

Language:TeXMIT010

dense_flow

Tools to extract dense optical flow from videos, based on OpenCV

Language:C++MIT000

FCRN-DepthPrediction

Deeper Depth Prediction with Fully Convolutional Residual Networks (FCRN)

Language:PythonBSD-2-Clause010

GeoNet

Code for GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018)

Language:PythonMIT010

models

Models and examples built with TensorFlow

Language:PythonApache-2.0010

monodepth

Unsupervised single image depth prediction with CNNs

Language:PythonNOASSERTION010

ORB_SLAM2

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

Language:C++NOASSERTION010

QICQ

计网大作业

Language:C#010

SfMLearner

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

Language:Jupyter NotebookMIT010

shadowsocks-heroku

免费使用 Heroku 部署 shadowsocks

Language:CoffeeScriptMIT010

single-cell-tutorial

Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

Language:Jupyter Notebook010

sparse-to-dense

ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image"

Language:LuaNOASSERTION000

spatial-cell

Human-in-the-loop spatial data Analysis with lasso

Language:Python000

three-js-som

A visualization of a 1D/2D/3D self-organizing map neural network learning to fit a 3D dataset. Made with three.js.

MIT000

vae_tutorial

Caffe code to accompany my Tutorial on Variational Autoencoders

Language:PythonMIT000