Learn instance weight by reliability propagation on an adaptive graph
-
Updated
Jan 15, 2018 - Scala
Learn instance weight by reliability propagation on an adaptive graph
Pytorch Implementation of GNN Meta Attack paper.
A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
Baseline collective classification library
Canonical coordinate by universal covering space
MATLAB code for the ICDM paper "Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view Clustering"
Python implementation of the Structured Graph Learning (SGL) algorithm by Kumar et. al (2019, https://papers.nips.cc/paper/9339-structured-graph-learning-via-laplacian-spectral-constraints)
Code for the paper "Multi-view Graph Learning by Joint Modeling of Consistency and Inconsistency"
The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
Anshul Yadav's BTech Thesis
Papers related with dynamic/time-series graph
A stereo-aware attention graph neural network
A data-driven approach for Gin Rummy hand evaluation
Multi-class Classification with fine-tuned BERT & GNN
Stratification of multi-label datasets
Graph construction from data using Non Negative Kernel Regression
Recurrent multigraph integrator network using graph neural network.
MyLectureNotes on Pascal Welke's lecture "Graph Representation Learning" (winter term 2021/2022)
Social Network Analysis with the Facebook100 Dataset
PyTorch-Geometric Implementation of MarkovGNN method published in Graph Learning@WWW 2022 titled "MarkovGNN: Graph Neural Networks on Markov Diffusion"
Add a description, image, and links to the graph-learning topic page so that developers can more easily learn about it.
To associate your repository with the graph-learning topic, visit your repo's landing page and select "manage topics."