Hi! I am a PhD Student at the Institute for Adaptive and Neural Computation and part of the APRIL research lab in Edinburgh, supervised by Dr. Antonio Vergari and Dr. Iain Murray. My research interests include (tractable) generative models, neurosymbolic AI, and anything that can be found at their intersection.

Curriculum Vitae

Featured publications

For a complete list refer to the Semantic Scholar profile.

• Subtractive Mixture Models via Squaring: Representation and Learning
  L. Loconte, A. M. Sladek, S. Mengel, M. Trapp, A. Solin, N. Gillis, A. Vergari.
  ICLR 2024. Spotlight (top 5%).
  
  tl;dr: We propose to build (deep) subtractive mixture models by squaring circuits. We theoretically prove their expressiveness by deriving an exponential lowerbound on the size of circuits with positive parameters only.
  
• How to Turn Your Knowledge Graph Embeddings into Generative Models
  L. Loconte, N. Di Mauro, R. Peharz, A. Vergari.
  NeurIPS 2023. Oral (top 0.6%).
  
  tl;dr: KGE models such as CP, RESCAL, TuckER, ComplEx can be re-interpreted as circuits to unlock their generative capabilities, scaling up learning and guaranteeing the satisfaction of logical constraints by design.