Renato Lui Geh

I am a Computer Science PhD student at the University of California, Los Angeles. I'm fortunate to be advised by Prof. Guy Van den Broeck and be a part of StarAI Lab.

I'm interested in the intersection of probabilistic machine learning and symbolic reasoning. Some specific interests of mine include (but are not limited to): tractable probabilistic models, logic and probabilistic circuits, knowledge representation and compilation, logic and probabilistic programming (and their intersection), weighted model counting, weighted model integration, and probabilistic graphical models.

Previously, I received my MSc and BSc in Computer Science under the supervision of Prof. Denis Deratani Mauá at the University of São Paulo in my home country Brazil 🇧🇷.

You can reach me at renatolg@cs.cs.ucla.ucla.edu.

Publications

• Where is the signal in tokenization space?
  Renato Lui Geh, Honghua Zhang, Kareem Ahmed, Benjie Wang, Guy Van den Broeck.
  EMNLP 2024.
  Oral presentation.
  [abs]
• dPASP: A Probabilistic Logic Programming Environment For Neurosymbolic Learning and Reasoning
  Renato Lui Geh, Jonas L. Gonçalves, Igor Cataneo Silveira, Denis D. Mauá, Fabio Cozman.
  KR 2024.
  [abs]
• LUNCH: an Answer Set Programming System for Course Scheduling
  Ana Y. F. de Lima, Briza M. D. de Sousa, Daniel P. Cardeal, Jessica Y. N. Sato, Lorenzo B. Salvador, Renato L. Geh, Bruna Bazaluk.
  ENIAC 2023.
  [doi]
• Scalable Learning of Probabilistic Circuits
  Renato Lui Geh (advisor: Denis D. Mauá).
  MSc thesis.
  Best MSc in AI at CTDIAC@BRACIS 2022!
  Best MSc in Computing at CTD@CSBC 2023!
  [slides]
• Fast And Accurate Learning of Probabilistic Circuits by Random Projections
  Renato L. Geh, Denis D. Mauá.
  TPM Workshop 2021.
  [talk] [slides] [poster]
• Learning Probabilistic Sentential Decision Diagrams Under Logic Constraints by Sampling and Averaging"
  Renato L. Geh, Denis D. Mauá.
  UAI 2021.
  [pmlr] [talk] [slides] [poster]
• Learning Probabilistic Sentential Decision Diagrams by Sampling
  Renato Geh, Denis Mauá, Alessandro Antonucci.
  KDMiLe 2020.
  [doi] [talk] [slides]
• End-To-End Imitation Learning of Lane Following Policies Using Sum-Product Networks
  Renato L. Geh, Denis D. Mauá.
  ENIAC 2019.
  [doi] [poster]