Pinned Repositories
ActivePathways_Copy
test
AGE
Adapted fromthe KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"
Best-README-Template
An awesome README template to jumpstart your projects!
BIDD
Bio info drug discovery
build-your-own-x
🤓 Build your own (insert technology here)
coding-interview-university
A complete computer science study plan to become a software engineer.
Deepan
Cluster patient based on their multiomics data utilizing graph autoencoders
EMOGI-NSCLC
An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.
ferdinand-popp
Config files for my GitHub profile.
MOGCN
Placeholder for code of the Master Thesis and Poster Presentation ICSB 2022 Berlin
ferdinand-popp's Repositories
ferdinand-popp/Deepan
Cluster patient based on their multiomics data utilizing graph autoencoders
ferdinand-popp/EMOGI-NSCLC
An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.
ferdinand-popp/MOGCN
Placeholder for code of the Master Thesis and Poster Presentation ICSB 2022 Berlin
ferdinand-popp/ActivePathways_Copy
test
ferdinand-popp/AGE
Adapted fromthe KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"
ferdinand-popp/Best-README-Template
An awesome README template to jumpstart your projects!
ferdinand-popp/BIDD
Bio info drug discovery
ferdinand-popp/build-your-own-x
🤓 Build your own (insert technology here)
ferdinand-popp/coding-interview-university
A complete computer science study plan to become a software engineer.
ferdinand-popp/ferdinand-popp
Config files for my GitHub profile.
ferdinand-popp/ferdinand-popp.github.io
Personal Webpage
ferdinand-popp/graphml-tutorials
Forked: Tutorials for Machine Learning on Graphs
ferdinand-popp/graphrag-biomed
COPY: A modular graph-based Retrieval-Augmented Generation (RAG) system for biomedical communication
ferdinand-popp/IntegrativeVAEs
Variational autoencoders for cancer data integration
ferdinand-popp/introtodeeplearning
Lab Materials for MIT 6.S191: Introduction to Deep Learning
ferdinand-popp/linear_graph_autoencoders
Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)
ferdinand-popp/MEDS-Detection
Hackathon Q-Summit Result of Team MEDS | Detecting flawed entries in medical health records
ferdinand-popp/MGAE
Implementation of the CIKM-17 paper “MGAE: Marginalized Graph Autoencoder for Graph Clustering”
ferdinand-popp/MMGL-NSCLC
Forked: Multi-modal Graph learning for Disease Prediction (IEEE Trans. on Medical imaging, TMI2022)
ferdinand-popp/NeoGPT-Biomedical
Context-aware knowledge-graph based chatbot using GPT4 and Neo4j
ferdinand-popp/nvidia-sniper
🎯 Autonomously buy Nvidia Founders Edition GPUs as soon as they become available.
ferdinand-popp/pandasgui
A GUI for Pandas DataFrames
ferdinand-popp/PHATE
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
ferdinand-popp/pycaret
An open source, low-code machine learning library in Python
ferdinand-popp/PYKEEN_LUNG
ferdinand-popp/SurvivalNet
Deep learning survival models
ferdinand-popp/TCGAIntegrator
Python utilities for building integrated views of TCGA data.