10 citations · 71 across the 49 of their papers we have counts for
8 papers · 1 filter
Scaling up Probabilistic Inference in Linear and Non-Linear Hybrid Domains by Leveraging Knowledge Compilation
Anton Fuxjaeger, Vaishak Belle
Weighted model integration (WMI) extends weighted model counting (WMC) in providing a computational abstraction for probabilistic inference in mixed discrete-continuous domains. WM…
Learning Tractable Probabilistic Models for Moral Responsibility and Blame
Lewis Hammond, Vaishak Belle
Moral responsibility is a major concern in autonomous systems, with applications ranging from self-driving cars to kidney exchanges. Although there have been recent attempts to for…
Abstracting Probabilistic Models: A Logical Perspective
Vaishak Belle
Abstraction is a powerful idea widely used in science, to model, reason and explain the behavior of systems in a more tractable search space, by omitting irrelevant details. While…
Reasoning about Discrete and Continuous Noisy Sensors and Effectors in Dynamical Systems
Vaishak Belle, Hector J. Levesque
Among the many approaches for reasoning about degrees of belief in the presence of noisy sensing and acting, the logical account proposed by Bacchus, Halpern, and Levesque is perha…
On Plans With Loops and Noise
Vaishak Belle
In an influential paper, Levesque proposed a formal specification for analysing the correctness of program-like plans, such as conditional plans, iterative plans, and knowledge-bas…
Learning Probabilistic Logic Programs in Continuous Domains
Stefanie Speichert, Vaishak Belle
The field of statistical relational learning aims at unifying logic and probability to reason and learn from data. Perhaps the most successful paradigm in the field is probabilisti…
Tractable Querying and Learning in Hybrid Domains via Sum-Product Networks
Andreas Bueff, Stefanie Speichert, Vaishak Belle
Probabilistic representations, such as Bayesian and Markov networks, are fundamental to much of statistical machine learning. Thus, learning probabilistic representations directly…
Probabilistic Planning by Probabilistic Programming
Vaishak Belle
Automated planning is a major topic of research in artificial intelligence, and enjoys a long and distinguished history. The classical paradigm assumes a distinguished initial stat…