Junliang Li
Junliang Li
LSTM-Load-Forecasting
Implementation of Electric Load Forecasting Based on LSTM(BiLSTM). Including Univariate-SingleStep forecasting, Multivariate-SingleStep forecasting and Multivariate-MultiStep forecasting.
cnn-dogs-vs-cats
Implementation of cats-vs-dogs based on CNN.
FedAvg-numpy-pytorch-tff
Three implementations of FedAvg: numpy, pytorch and tensorflow federated.
FedPer
PyTorch implementation of FedPer (Federated Learning with Personalization Layers).
FedProx-PyTorch
PyTorch implementation of FedProx (Federated Optimization for Heterogeneous Networks, MLSys 2020).
GNNs-for-Node-Classification
Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Graph Attention Network), which will continue to be updated in the...
LSTM-MultiStep-Forecasting
Implementation of Electric Load Forecasting Based on LSTM (BiLSTM). Including direct-multi-output forecasting, single-step-scrolling forecasting, multi-model-single-step forecasting, multi-model-scrol...
node2vec
Implement the node2vec algorithm using Python
Per-FedAvg
PyTorch implementation of Per-FedAvg (Personalized Federated Learning: A Meta-Learning Approach).