We are super proud of our colleague Madalina who defended two weeks ago her PhD at the Université libre de Bruxelles.
She studied unsupervised analysis of RNA sequencing protocols data, and brilliantly succeeded.
You rock Madalina!
Congrats, Dr Ciortan!
Releated Posts
Augment to Interpret: Unsupervised and Inherently Interpretable Graph Embeddings
In this paper, we study graph representation learning and show that data augmentation that preserves semantics can be learned and used to produce interpretations. Our framework, which we named INGENIOUS, creates inherently interpretable embeddings and eliminates the need for costly additional post-hoc analysis.
SANGEA: Scalable and Attributed Network Generation
In this paper, we present SANGEA, a sizeable synthetic graph generation framework that extends the applicability of any SGG to large graphs.
By first splitting the large graph into communities, SANGEA trains one SGG per community, then links the community graphs back together to create a synthetic large graph.