caomaowsh Goto Github PK

algo-on-graphs

Algorithms in Graph Theory written in Java, C++, and Python

awesome-network-analysis

A curated list of awesome network analysis resources.

bionev

Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations" (Bioinformatics 2020)

classifiertoolbox

A MATLAB toolbox for classifier: Version 1.0.7

community-detection-code

continual-learning

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).

continual-learning-benchmark

Evaluate three types of task shifting with popular continual learning algorithms.

coursera-ml-py

Python programming assignments for Machine Learning by Prof. Andrew Ng in Coursera

ddoutlier

A MATLAB version of DDOutlier

deep-belief-network

A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility

deep-learning-from-scratch

深度学习入门-基于Python的理论与实现》，包含源代码和高清PDF(带书签)；慕课网imooc《深度学习之神经网络(CNN-RNN-GAN)算法原理-实战》

deepsem

detectioncausalrelationshipstimeseries

Code for paper "A method for detecting causal relationships between discrete time series using Transfer entropy and K2-Algorithm: A case study on the plant-wide simulation Tennessee Eastman Process"

ggnn.pytorch

A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)

graph-neural-networks-for-drug-discovery

l2c

Learning to Cluster. A deep clustering strategy.

learntf

learning code with tf

lhy_machine_learning

李宏毅2021春季机器学习课程课件及作业

lstm-autoencoders

Anomaly detection for streaming data using autoencoders

machinelearning

matlab

matlab-toolboxes

Contains all my Matlab toolboxes.

maximally_interfered_retrieval

Codebase for "Online Continual Learning with Maximally Interfered Retrieval"

medium_notebook

Repository containing notebooks of my posts on Medium

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

nnksc

Non-negative Kernel Sparse Coding algorithm for semantic dictionary learning in feature space.

sae-in-python

a python implement of the paper Semantic Autoencoder for Zero-Shot Learning

ss-gcns

[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

ssdkl

Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance

ssvep-neural-generative-models

Code to accompany our International Joint Conference on Neural Networks (IJCNN) paper entitled - Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification