Pinned Repositories
AttentionWalk
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
BaiDuBigData19-URFC
my solution with 0.67 accuracy
caffe
This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors
ClusterGCN
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
convnet
based on cuda-convnet
NRLPapers
Must-read papers on network representation learning (NRL) / network embedding (NE)
RaymondHLIU.github.io
personal webpage
sparse-sharing
Codes for "Learning Sparse Sharing Architectures for Multiple Tasks"
RaymondHLIU's Repositories
RaymondHLIU/NRLPapers
Must-read papers on network representation learning (NRL) / network embedding (NE)
RaymondHLIU/RaymondHLIU.github.io
personal webpage
RaymondHLIU/sparse-sharing
Codes for "Learning Sparse Sharing Architectures for Multiple Tasks"
RaymondHLIU/AttentionWalk
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
RaymondHLIU/BaiDuBigData19-URFC
my solution with 0.67 accuracy
RaymondHLIU/ClusterGCN
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
RaymondHLIU/CTR_Prediction
CTR prediction using FM FFM and DeepFM
RaymondHLIU/DeepCTR
Easy-to-use,Modular and Extendible package of deep-learning based CTR models.DeepFM,DeepInterestNetwork(DIN),DeepCrossNetwork(DCN),AttentionalFactorizationMachine(AFM),Neural Factorization Machine(NFM),AutoInt
RaymondHLIU/deepwalk
DeepWalk - Deep Learning for Graphs
RaymondHLIU/disentangling-vae
Experiments for understanding disentanglement in VAE latent representations
RaymondHLIU/disentanglment
Experiments with beta-VAE to learn disentangled representations from the data
RaymondHLIU/GEM
RaymondHLIU/GraphGAN
A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)
RaymondHLIU/LINE
LINE: Large-scale information network embedding
RaymondHLIU/LlamaGym
Fine-tune LLM agents with online reinforcement learning
RaymondHLIU/models
Models and examples built with TensorFlow
RaymondHLIU/NetMF
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
RaymondHLIU/node2vec
RaymondHLIU/powerful-gnns
How Powerful are Graph Neural Networks?
RaymondHLIU/SDNE
This is a implementation of SDNE (Structural Deep Network embedding)
RaymondHLIU/sdne-keras
Keras implementation of Structural Deep Network Embedding, KDD 2016
RaymondHLIU/Serving
A flexible, high-performance carrier for machine learning models（『飞桨』服务化部署框架）
RaymondHLIU/T-GCN
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
RaymondHLIU/Taxi-Demand-Prediction-New-York-City
A Machine Learning Case Study to predict the Demand of Yellow Taxi in New York City at given location and at a given time interval.
RaymondHLIU/tensorflow-DeepFM
Tensorflow implementation of DeepFM for CTR prediction.
RaymondHLIU/tgn
TGN: Temporal Graph Networks
RaymondHLIU/transformer-xl
RaymondHLIU/UFUG1601
RaymondHLIU/UrbanRegionFunctionClassification
第五届百度西安交大大数据竞赛 城市区域功能分类 Baseline
RaymondHLIU/wide_deep
Wide and Deep Learning for CTR Prediction in tensorflow