StoneSongLucky

Pinned Repositories

Awesome-Dynamic-Network-Embedding
dynamic/temporal network embedding
10
DSWM
The novel distance called dynamic subwindow matching (DSWM) is to directly calculate the distance between two seismic waveforms with different lengths. A supervised seismic facies analysis method called K-nearest neighbors (KNN)-DSWM is presented for analyzing synthetic seismic data.
Language:MATLAB10
Private_Preserving_Outlier_Behavior_Detection
Private Preserving Outlier Behavior Modeling powered by Graph Analysis and Multilayer Network Embedding
Language:Python10

StoneSongLucky/DSWM
The novel distance called dynamic subwindow matching (DSWM) is to directly calculate the distance between two seismic waveforms with different lengths. A supervised seismic facies analysis method called K-nearest neighbors (KNN)-DSWM is presented for analyzing synthetic seismic data.
Language:MATLAB1
StoneSongLucky/Awesome-Dynamic-Network-Embedding
dynamic/temporal network embedding
1
StoneSongLucky/Private_Preserving_Outlier_Behavior_Detection
Private Preserving Outlier Behavior Modeling powered by Graph Analysis and Multilayer Network Embedding
Language:Python1