This is your work, valued

Aleksandar Bojchevski

Expert
@abojchevski

Professor at the University of Cologne. Trustworthy Machine Learning & ML on Graphs.

abojchevski.github.io/

graph2gauss. Gaussian node embeddings. Implementation of "Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking".

180

node_embedding_attack. Adversarial Attacks on Node Embeddings via Graph Poisoning

59

sparse_smoothing. Implementation of the certificates proposed in the paper "Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More"

37

rsc. Robust Spectral Clustering. Implementation of "Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings".

26

paican. Implementation of "Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure".

25

graph_cert. Certifiable Robustness to Graph Perturbations

14

edward. A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.

2

ogb. Benchmark datasets, data loaders, and evaluators for graph machine learning

2

nips-scraper. Scrapes the abstracts to NIPS 2017 papers.

1

CSrankings. A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

1

pymc3. Probabilistic Programming in Python. Uses Theano as a backend, supports NUTS and ADVI.

1

pytorch_geometric. Graph Neural Network Library for PyTorch

1