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Found 5 papers, 2 papers with code
Scalable Coupling of Deep Learning with Logical Reasoning
In the ongoing quest for hybridizing discrete reasoning with neural nets, there is an increasing interest in neural architectures that can learn how to solve discrete reasoning or optimization problems from natural inputs.
Efficient semidefinite bounds for multi-label discrete graphical models
By concisely representing a joint function of many variables as the combination of small functions, discrete graphical models (GMs) provide a powerful framework to analyze stochastic and deterministic systems of interacting variables.
Exact and approximate inference in graphical models: variable elimination and beyond
We illustrate the techniques reviewed in this article on benchmarks of inference problems in genetic linkage analysis and computer vision, as well as on hidden variables restoration in coupled Hidden Markov Models.
Tractability and Decompositions of Global Cost Functions
A global cost function is called tractable projection-safe when applying an EPT to it is tractable and does not break the tractability property.
Bounds Arc Consistency for Weighted CSPs
Motivated by the resolution of an RNA gene localization problem inside large genomic sequences, and in the spirit of bounds consistency for large domains in crisp CSPs, we introduce soft bounds arc consistency, a new weighted local consistency specifically designed for WCSP with very large domains.
