Jingfei-Liu
Bayesian Machine Learning and its Application (PhD Candidate from Hunan University) liujingfei@hnu.edu.cn
Chang Sha City HuNan Province P.R. China
Pinned Repositories
arxiv-latex-cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
BfROpenLab
BfR KNIME extensions (FoodChain-Lab, KNIME Nodes for GIS and Graph Visualization, KNIME Nodes for Nonlinear Regression, BfR Network Mining Extensions, PMM-Lab Lite)
black
The uncompromising Python code formatter
dbn_tf
RBM/DBN implementation with tensorflow attempt project
deep-learning-uncertainty
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
denser-models
deterministic-variational-inference
Sample code for running deterministic variational inference to train Bayesian neural networks
DPPy
Python toolbox for sampling Determinantal Point Processes
edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
emcee
The Python ensemble sampling toolkit for affine-invariant MCMC
Jingfei-Liu's Repositories
Jingfei-Liu/arxiv-latex-cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Jingfei-Liu/BfROpenLab
BfR KNIME extensions (FoodChain-Lab, KNIME Nodes for GIS and Graph Visualization, KNIME Nodes for Nonlinear Regression, BfR Network Mining Extensions, PMM-Lab Lite)
Jingfei-Liu/black
The uncompromising Python code formatter
Jingfei-Liu/deep-learning-uncertainty
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
Jingfei-Liu/denser-models
Jingfei-Liu/deterministic-variational-inference
Sample code for running deterministic variational inference to train Bayesian neural networks
Jingfei-Liu/DPPy
Python toolbox for sampling Determinantal Point Processes
Jingfei-Liu/edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Jingfei-Liu/emcee
The Python ensemble sampling toolkit for affine-invariant MCMC
Jingfei-Liu/fashion-mnist
A MNIST-like fashion product database. Benchmark :point_right:
Jingfei-Liu/HpBandSter
a distributed Hyperband implementation on Steroids
Jingfei-Liu/IIC
Invariant Information Clustering for Unsupervised Image Classification and Segmentation
Jingfei-Liu/libpku
北京大学课程资料整理
Jingfei-Liu/mathematics_dataset
Jingfei-Liu/nevergrad
A Python toolbox for performing gradient-free optimization
Jingfei-Liu/pingouin
Statistical package in Python based on Pandas
Jingfei-Liu/playground
Play with neural networks!
Jingfei-Liu/PRML
PRML algorithms implemented in Python
Jingfei-Liu/PRMLT
Matlab code for machine learning algorithms in book PRML
Jingfei-Liu/psychic-lamp
we are good at create impossible
Jingfei-Liu/pyro
Deep universal probabilistic programming with Python and PyTorch
Jingfei-Liu/pyrobot
PyRobot: An Open Source Robotics Research Platform
Jingfei-Liu/python-cheatsheet
Comprehensive Python Cheatsheet
Jingfei-Liu/python-implementation-for-HPHO
It is a python implementation for HPHO
Jingfei-Liu/pytorch-meta
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Jingfei-Liu/quadpy
Numerical integration (quadrature, cubature) in Python
Jingfei-Liu/RBM_DBN
Experimenting with RBMs using scikit-learn on MNIST and simulating a DBN using Keras.
Jingfei-Liu/the-craft-of-selfteaching
One has no future if one couldn't teach themself.
Jingfei-Liu/trax
Trax — your path to advanced deep learning
Jingfei-Liu/yolov3
YOLOv3 in PyTorch > ONNX > CoreML > iOS