We propose a simple approach which combines the strengths of probabilist...
Explainable machine learning and artificial intelligence models have bee...
Combining logic and probability has been a long standing goal of AI. Mar...
Lifted inference reduces the complexity of inference in relational
proba...
We propose a simple and easy to implement neural network compression
alg...
Due to the intractable nature of exact lifted inference, research has
re...
The paper investigates parameterized approximate message-passing schemes...
In this paper, we present structured message passing (SMP), a unifying
f...
In this paper, we present a Branch and Bound algorithm called QuickBB fo...
In this paper, we consider Hybrid Mixed Networks (HMN) which are Hybrid
...
This paper describes a general framework called Hybrid Dynamic Mixed Net...
The paper introduces AND/OR importance sampling for probabilistic graphi...
Computing the probability of a formula given the probabilities or weight...
Many representation schemes combining first-order logic and probability ...
Inference in graphical models consists of repeatedly multiplying and sum...