WebNov 22, 2024 · GraphGAN: Graph Representation Learning with Generative Adversarial Nets 22 Nov 2024 · Hongwei Wang , Jia Wang , Jialin Wang , Miao Zhao , Wei-Nan … WebGraphGAN-pytorch/src/evaluation/recommendation.py Go to file Cannot retrieve contributors at this time 63 lines (52 sloc) 2.52 KB Raw Blame import math import numpy as np import pandas as pd import sys from sklearn.multiclass import OneVsRestClassifier from sklearn.linear_model import LogisticRegression from sklearn.metrics import accuracy_score

G_loss will be negative value when I am training the model #1 - Github

WebNov 22, 2024 · In this paper, we propose GraphGAN, an innovative graph representation learning framework unifying above two classes of methods, in which the generative model and discriminative model play a game-theoretical minimax game. WebGenerating graphs from noise. Contribute to siddsax/graphGAN development by creating an account on GitHub. cynthia langford

He-jerry/PatchGAN - Github

- GitHub - THUDM/GraphSGAN: Implementation of "GraphSGAN", a GAN-based semi-supervised learning algorithm for graph data. Implementation of "GraphSGAN", a GAN-based semi-supervised learning algorithm for graph data. See more The codes are written under Python==2.7 and pytorch~=3. If you want to run it in other environments, minor changes might be needed. See more will run a example, banchmark cora task. The programme takes FeatureGraphDataset as input and cora.dataset is built from FeatureGraphDataset.py. … See more http://konstantinosx.github.io/graphgen-project/ cynthia langrall