Pinned Repositories
3a
Solutions for Introduction to Algorithms
async_deep_reinforce
Asynchronous Methods for Deep Reinforcement Learning
BART
The BART Project: Benchmarking Algorithms for (data) Repairing and Translation
book-1
CLRS-Exercises
CNN-parallel
Parallel Implementation of CNN on all major framework - Keras, Tensorflow etc.
Coursera-Data-Mining
Data Mining - University of Illinois at Urbana-Champaign
courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
cs140
CS61B
UC Berkeley CS 61B Spring 2014
Patrickgsheng's Repositories
Patrickgsheng/async_deep_reinforce
Asynchronous Methods for Deep Reinforcement Learning
Patrickgsheng/BART
The BART Project: Benchmarking Algorithms for (data) Repairing and Translation
Patrickgsheng/book-1
Patrickgsheng/Coursera-Data-Mining
Data Mining - University of Illinois at Urbana-Champaign
Patrickgsheng/CS61B
UC Berkeley CS 61B Spring 2014
Patrickgsheng/Data-Structures
This repository will contain my work from the Master Algorithmic Programming Techniques Specialization that was created by UC San Diego and delivered through Coursera.
Patrickgsheng/datasci_course_materials
Public repository for course materials for the Data Science at Scale Specialization at Coursera
Patrickgsheng/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Patrickgsheng/dlwpt-code
Code for the book Deep Learning with PyTorch by Eli Stevens and Luca Antiga.
Patrickgsheng/GAT
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
Patrickgsheng/gcn_Co-Training_Self-Training
Implementation of Graph Convolutional Networks in TensorFlow
Patrickgsheng/GCN_detection_benchmark
Patrickgsheng/GNNPapers
Must-read papers on graph neural networks (GNN)
Patrickgsheng/Graph_Sampling
Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.
Patrickgsheng/GraphSAGE_Benchmark
Assessing a benchmark for dirty data detection in graphs using GraphSAGE.
Patrickgsheng/GraphSageDetectionBenchmark
Patrickgsheng/HAN
Heterogeneous Graph Neural Network
Patrickgsheng/KDD-2019-Hands-on
DGL tutorial in KDD 2019
Patrickgsheng/KDD2019-HandsOn-Tutorial
KDD 2019 hands-on tutorial
Patrickgsheng/lgcn
Patrickgsheng/numpy-ml
Machine learning, in numpy
Patrickgsheng/ppnp
PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank".
Patrickgsheng/pyGAT
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
Patrickgsheng/pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation
Patrickgsheng/Representation-Learning-on-Heterogeneous-Graph
Representation-Learning-on-Heterogeneous-Graph
Patrickgsheng/tensorflow
Computation using data flow graphs for scalable machine learning
Patrickgsheng/tensorflowbook
Patrickgsheng/tensorspark
TensorFlow on Spark
Patrickgsheng/TopKDensestSubgraph
Fully Dynamic Algorithm for Top-k Densest Subgraphs
Patrickgsheng/Virtual-Machine-Administration-with-Xen-Project-Ver-1.0
Virtual Machine Administration with Xen Project Ver 1.0