Composicionalidade causal e modelos energéticos | PROMPT #04

Causal Compositionality and Energy-Based Causal Models

Ricardo Silva (University College London)

Dr. Ricardo Silva is a Senior Lecturer in the Department of Statistical Science, Adjunct Faculty in the Gatsby Computational Neuroscience Unit, and in the management group of the Centre for Computational Statistics and Machine Learning (CSML) at UCL.

He is also in the management group of the EPSRC Network on Computational Statistics and Machine Learning and a fellow of the Alan Turing Institute. Dr Silva has extensive experience in research in machine learning, in particular in areas such as graphical models, latent variable models and causality. During his PhD at Carnegie Mellon University, Dr Silva laid off some early work on causal structure identification for models with unobserved variables. Dr Silva introduced new approaches for graphical model construction and inference, models for network data in prediction problems and information retrieval and developed inference algorithms for complex distributions and causal models, among other contributions.

Data: 25 de fevereiro de 2025
Horário: 14h30
Local: Auditório do Laboratório Galileu – sede do BI0S, Rua Josiah Willard Gibbs, 85 – Cidade Universitária, Campinas – SP, CEP:13083-841 (Unicamp)