
Logical Interpretations of Autoencoders
The unification of lowlevel perception and highlevel reasoning is a lo...
read it

Interventions and Counterfactuals in Tractable Probabilistic Models: Limitations of Contemporary Transformations
In recent years, there has been an increasing interest in studying causa...
read it

SMT + ILP
Inductive logic programming (ILP) has been a deeply influential paradigm...
read it

On Constraint Definability in Tractable Probabilistic Models
Incorporating constraints is a major concern in probabilistic machine le...
read it

Experiential AI
Experiential AI is proposed as a new research agenda in which artists an...
read it

Semiring Programming: A Framework for Search, Inference and Learning
To solve hard problems, AI relies on a variety of disciplines such as lo...
read it

Robot Location Estimation in the Situation Calculus
Location estimation is a fundamental sensing task in robotic application...
read it

Reasoning about Probabilities in Dynamic Systems using Goal Regression
Reasoning about degrees of belief in uncertain dynamic worlds is fundame...
read it

MultiAgent OnlyKnowing Revisited
Levesque introduced the notion of onlyknowing to precisely capture the ...
read it

Probabilistic Planning by Probabilistic Programming
Automated planning is a major topic of research in artificial intelligen...
read it

Tractable Querying and Learning in Hybrid Domains via SumProduct Networks
Probabilistic representations, such as Bayesian and Markov networks, are...
read it

The Symbolic Interior Point Method
A recent trend in probabilistic inference emphasizes the codification of...
read it

Learning Probabilistic Logic Programs in Continuous Domains
The field of statistical relational learning aims at unifying logic and ...
read it

Reasoning about Discrete and Continuous Noisy Sensors and Effectors in Dynamical Systems
Among the many approaches for reasoning about degrees of belief in the p...
read it

Abstracting Probabilistic Relational Models
Abstraction is a powerful idea widely used in science, to model, reason ...
read it

Deep Tractable Probabilistic Models for Moral Responsibility
Moral responsibility is a major concern in automated decisionmaking, wi...
read it

On Plans With Loops and Noise
In an influential paper, Levesque proposed a formal specification for an...
read it

Scaling up Probabilistic Inference in Linear and NonLinear Hybrid Domains by Leveraging Knowledge Compilation
Weighted model integration (WMI) extends weighted model counting (WMC) i...
read it

Learning Tractable Probabilistic Models in Open Worlds
Largescale probabilistic representations, including statistical knowled...
read it

Implicitly Learning to Reason in FirstOrder Logic
We consider the problem of answering queries about formulas of firstord...
read it

The Quest for Interpretable and Responsible Artificial Intelligence
Artificial Intelligence (AI) provides many opportunities to improve priv...
read it

Fairness in Machine Learning with Tractable Models
Machine Learning techniques have become pervasive across a range of diff...
read it

A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains
Finitestate controllers (FSCs), such as plans with loops, are powerful ...
read it
Vaishak Belle
is this you? claim profile