ferdinand-popp's Projects
test
Adapted fromthe KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"
An awesome README template to jumpstart your projects!
Bio info drug discovery
🤓 Build your own (insert technology here)
A complete computer science study plan to become a software engineer.
Cluster patient based on their multiomics data utilizing graph autoencoders
An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.
Config files for my GitHub profile.
Personal Webpage
Forked: Tutorials for Machine Learning on Graphs
Variational autoencoders for cancer data integration
Lab Materials for MIT 6.S191: Introduction to Deep Learning
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)
Hackathon Q-Summit Result of Team MEDS | Detecting flawed entries in medical health records
Implementation of the CIKM-17 paper “MGAE: Marginalized Graph Autoencoder for Graph Clustering”
Forked: Multi-modal Graph learning for Disease Prediction (IEEE Trans. on Medical imaging, TMI2022)
Placeholder for code of the Master Thesis and Poster Presentation ICSB 2022 Berlin
Context-aware knowledge-graph based chatbot using GPT4 and Neo4j
🎯 Autonomously buy Nvidia Founders Edition GPUs as soon as they become available.
A GUI for Pandas DataFrames
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
An open source, low-code machine learning library in Python
Deep learning survival models
Python utilities for building integrated views of TCGA data.