16 citations · 60 across the 12 of their papers we have counts for
12 papers
Scaling Neuro-symbolic Problem Solving: Solver-Free Learning of Constraints and Objectives
Marianne Defresne, Romain Gambardella, Sophie Barbe +1
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…
Scalable Coupling of Deep Learning with Logical Reasoning
Marianne Defresne, Sophie Barbe, Thomas Schiex
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…
Efficient semidefinite bounds for multi-label discrete graphical models
Valentin Durante, George Katsirelos, Thomas Schiex
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 stochast…
Exact and approximate inference in graphical models: variable elimination and beyond
Nathalie Peyrard, Marie-Josée Cros, Simon de Givry +5
Probabilistic graphical models offer a powerful framework to account for the dependence structure between variables, which is represented as a graph. However, the dependence betwee…
Tractability and Decompositions of Global Cost Functions
David Allouche, Christian Bessiere, Patrice Boizumault +8
Enforcing local consistencies in cost function networks is performed by applying so-called Equivalent Preserving Transformations (EPTs) to the cost functions. As EPTs transform the…
Bounds Arc Consistency for Weighted CSPs
Matthias Zytnicki, Christine Gaspin, Simon de Givry +1
The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving problems involving both hard constraints and cost functions. It has been applied to va…