Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing

Abstract

Paper presentation.

Date
Jul 15, 2020 8:00 AM
Location
Online
Zhe Zeng
Zhe Zeng
Ph.D. student in AI

My research goal is to enable machine learning models to incorporate diverse forms of constraints into probabilistic inference and learning in a principled way, by combining machine learning (probabilistic modeling, neuro-symbolic AI, Bayesian deep learning) and formal methods.