frankuc's repositories
RpHGNN
Source code and dataset of the paper "Efficient Heterogeneous Graph Learning via Random Projection"
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
induen
Repo for detecting interrelated dense subgraphs in multilayer network (TKDE 2024)
DeepHypergraph
A pytorch library for graph and hypergraph computation.
Graph-Neural-Networks-With-Heterophily
This repository contains the resources on graph neural network (GNN) considering heterophily.
HyNT
Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers (KDD 2023)
awesome-self-supervised-learning-for-tabular-data
A collection of research materials on SSL for tabular data
GraphGym
Platform for designing and evaluating Graph Neural Networks (GNN)
CLIP
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
gbbs
GBBS: Graph Based Benchmark Suite
KNiNe
kNN graph construction in Spark using LSH.
SlimG
Code for paper "Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining" (KDD 2023)
GAWD
Code for paper "GAWD: Graph Anomaly Detection in Directed Weighted Graph Databases" (ASONAM 2021)
AutoAudit
Code for paper "AutoAudit: Mining Accounting and Time-Evolving Graphs" (Big Data 2020)
gen2Out
Code for paper "gen2Out: Detection and Ranking Generalized Anomalies" (Big Data 2021)
InfoShield
Code for paper "InfoShield: Generalizable Information-Theoretic Human-Trafficking Detection" (ICDE 2021)
pretrain-gnns
Strategies for Pre-training Graph Neural Networks
Awesome-GNN4TS
Awesome resources related to GNNs for Time Series Analysis (GNN4TS) 🔥 https://arxiv.org/abs/2307.03759
ADMNC
Spark implementation of the Anomaly Detection with Mixed Numerical and Categorical inputs (ADMNC) algorithm
algebird
Abstract Algebra for Scala
GPT-GNN
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
datasketch
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble
SDM2023_Graph_Data_Augmentation_Tutorial
Materials for SDM 2023 tutorial: Augmentation Methods for Graph Learning