Credal networks extend Bayesian networks to allow for imprecision in probability values.
Marginal MAP is a widely applicable mixed inference task that identifies the most likely …

Abstract Logical Credal Networks or LCNs is a recent probabilistic logic designed for
effective aggregation and reasoning over multiple sources of imprecise knowledge. An LCN …

Statistical inference is a powerful technique in various applications. Although many
statistical inference tools are available, answering inference queries involving complex …

The importance of designing proteins, such as high affinity antibodies, has become ever
more apparent. Computational Protein Design can cast such design problems as …

Exact inference of marginals in probabilistic graphical models (PGM) is known to be
intractable, necessitating the use of approximate methods. Most of the existing variational …

Influence diagrams provide a modeling and inference framework for sequential decision
problems, representing the probabilistic knowledge by a Bayesian network and the …

Sum-product networks are expressive efficient probabilistic graphical models that allow for
tractable marginal inference. Many tasks however require the computation of maximum-a …

Logical Credal Networks or LCNs were recently introduced as a powerful probabilistic logic
framework for representing and reasoning with imprecise knowledge. Unlike many existing …

Automated decision-making systems are increasingly being deployed in areas with high
personal and societal impact. This naturally led to growing interest in trustworthy artificial …

Influence diagrams (IDs) are graphical models for representing and reasoning with
sequential decision-making problems under uncertainty. Limited memory influence …