1 citations · 1 across the 4 of their papers we have counts for
5 papers
DPNL: A DPLL-based Algorithm for Probabilistic Neurosymbolic Learning
Thomas Jean-Michel Valentin, Pierre Genev{è}s, Luisa Sophie Werner +3
Probabilistic Neurosymbolic Learning (PNL) combines neural predictions with symbolic reasoning, enabling end-to-end learning from final-output supervision without labels for interm…
Optimizing Relational Queries over Array-Valued Data in Columnar Systems
Maroua Zeblah, Etienne Couritas, Sarah Chlyah +3
Modern analytical workloads increasingly combine relational data with array-valued attributes. While columnar database systems efficiently process such workloads, their ability to…
Efficient Iterative Programs with Distributed Data Collections
Sarah Chlyah, Nils Gesbert, Pierre Geneves +1
Big data programming frameworks have become increasingly important for the development of applications for which performance and scalability are critical. In those complex framewor…
Knowledge Enhanced Graph Neural Networks for Graph Completion
Luisa Werner, Nabil Layaïda, Pierre Genevès +1
Graph data is omnipresent and has a wide variety of applications, such as in natural science, social networks, or the semantic web. However, while being rich in information, graphs…
Distributed Evaluation of Graph Queries using Recursive Relational Algebra
Sarah Chlyah, Pierre Genevès, Nabil Layaïda
We present a system called Dist--RA for the distributed evaluation of recursive graph queries. Dist--RA builds on the recursive relational algebra and extends it with evaluat…