thjashin's Stars
soimort/you-get
:arrow_double_down: Dumb downloader that scrapes the web
geeeeeeeeek/electronic-wechat
:speech_balloon: A better WeChat on macOS and Linux. Built with Electron by Zhongyi Tong.
scipy/scipy
SciPy library main repository
pymc-devs/pymc
Bayesian Modeling and Probabilistic Programming in Python
HIPS/autograd
Efficiently computes derivatives of NumPy code.
scikit-image/scikit-image
Image processing in Python
skilion/onedrive
Free Client for OneDrive on Linux
jmschrei/pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
notofonts/noto-fonts
Noto fonts, except for CJK and emoji
SheffieldML/GPy
Gaussian processes framework in python
ilikenwf/apt-fast
apt-fast: A shellscript wrapper for apt that speeds up downloading of packages.
GPflow/GPflow
Gaussian processes in TensorFlow
google/prettytensor
Pretty Tensor: Fluent Networks in TensorFlow
lightning-viz/lightning
Data Visualization Server
percyliang/sempre
Semantic Parser with Execution
pystruct/pystruct
Simple structured learning framework for python
scottkosty/install-tl-ubuntu
Install script for TeX Live on Ubuntu
carpedm20/pixel-rnn-tensorflow
in progress
Calysto/matlab_kernel
Jupyter Kernel for Matlab
rewonc/pastalog
Simple, realtime visualization of neural network training performance.
dilinwang820/Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
casperkaae/parmesan
Variational and semi-supervised neural network toppings for Lasagne
HIPS/Probabilistic-Backpropagation
Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
lightning-viz/lightning-python
Python client for the lightning API
y0ast/VIMCO
Implementation of "Variational Inference for Monte Carlo Objectives"
jstraub/dpMMlowVar
Bayesian nonparametric small-variance asymptotic clustering algorithms
YingzhenLi/stochastic-EP
code for stochastic expectation propagation
tlienart/EPBP
Expectation Particle Belief Propagation code
naesseth/smc-pgm
Code implementing sequential Monte Carlo algorithms for probabilistic graphical models described in Naesseth, Lindsten and Schön, "Sequential Monte Carlo for Graphical Models", Advances in Neural Information Processing (NIPS) 27, 2014.
amueller/daimrf
Python interface for inference with LibDAI