Taming Discrete Integration via the Boon of Dimensionality

1 code implementation • NeurIPS 2020 • Jeffrey M. Dudek, Dror Fried, Kuldeep S. Meel

The proposed reduction is achieved via a significant increase in the dimensionality that, contrary to conventional wisdom, leads to solving an instance of the relatively simpler problem of model counting.

DPMC: Weighted Model Counting by Dynamic Programming on Project-Join Trees

1 code implementation • 20 Aug 2020 • Jeffrey M. Dudek, Vu H. N. Phan, Moshe Y. Vardi

We propose a unifying dynamic-programming framework to compute exact literal-weighted model counts of formulas in conjunctive normal form.

Tree Decomposition

Parallel Weighted Model Counting with Tensor Networks

1 code implementation • 28 Jun 2020 • Jeffrey M. Dudek, Moshe Y. Vardi

In this work, we explore the impact of multi-core and GPU use on tensor-network contraction for weighted model counting.

Data Structures and Algorithms

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions

1 code implementation • 12 Aug 2019 • Jeffrey M. Dudek, Leonardo Dueñas-Osorio, Moshe Y. Vardi

We show that tree decompositions can be used both to find carving decompositions and to factor tensor networks with high-rank, structured tensors.

Tensor Networks

ADDMC: Weighted Model Counting with Algebraic Decision Diagrams

1 code implementation • 11 Jul 2019 • Jeffrey M. Dudek, Vu H. N. Phan, Moshe Y. Vardi

We present an algorithm to compute exact literal-weighted model counts of Boolean formulas in Conjunctive Normal Form.