Program 2024

Tuesday November 12 – Sala 2: 701 (cuerpo central, piso 7) – Facultad de Ingeniería de la Universidad de la República.

All times are listed in Uruguay’s time (UTC-3)

To access the paper click on the Paper’s Title

To access the video of the Invited Talk click on the Talk’s Title

9:00 – 9:30	Opening Ceremony
9:30 – 10:30	Invited Talk – “Causal Representation Learning: Uncovering the Hidden World”. Prof. Kun Zhang
10:30-11:00	Coffee Break
11:00 – 12:45	Session I Fundamentals and Algorithms for Causal Discovery 15 minutes talk + 3 minutes quest.   A Framework for Practical Causal Discovery from Observational Data. – Gustavo F.V. de Oliveira, Fabrício A. Silva and Marcus H.S. Mendes   Causal Discovery: Improving Structure Learning using Knowledge and Synthetic data. – Jose Antonio Montero, Julio Muñoz-Benitez and Luis Enrique Sucar.   One-Class Learning for Text Causal Discovery through Hypergraph Neural Networks. – Marcos Paulo Silva Gôlo and Ricardo Marcacini.   Integrating Causal Inference into Dynamic Incentive Design. – Sebastián Bejos, Eduardo F. Morales, Luis Enrique Sucar and Enrique Munoz de Cote.   Semantic enrichment of causal graphs for strategic foresight. – Jože Rožanec and Gaël Gendron.   Causal Discovery of Non-Stationary Dynamic Causal Bayesian Networks. – Mario De Los Santos, Luis Enrique Sucar and Felipe Orihuela-Espina.
12:45 – 14:30	Lunch
14:30 – 16:00	Session II Applications   15 minutes talk + 3 minutes quest.   Preventing Collisions in Self-driving Cars using Probabilistic Logic Counterfactual Reasoning.  – Verónica Rodriguez, Héctor Avilés, Rubén Machucho, Alberto Reyes, Marco Negrete, Gabriel Ramírez, Alberto Petrilli, Ingridh Gracia, Gloria De-La-Garza, Karelly Rivera and Rafael Kiesel.   Visual robot navigation incorporating causal models in deep reinforcement learning. – Nilda Gabriela Xolo Tlapanco, Eduardo F. Morales, L. Enrique Sucar and J. Ernesto Gomez-Balderas. Combining Literature with Causal Discovery in Environmental Conflict.  – Maarten Vonk.   Discovering the causal structure of students’ entry into higher education in Chile from data. – Paulo Quinsacara, Billy Peralta and Pablo Schwarzenberg.   Exploring Connectivity in Parkinson’s Disease Using Graphical Models and fNIRS. – Samuel Montero-Hernandez and Edgar Guevara.
16:00 – 16:30	Coffee Break
16:30-17:30	Invited Talk – “Causal Discovery from Complicated Data”. Prof. David Danks
17:30 – 18:00	Discussion Panel / Closing Ceremony