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Semantic Strengthening of Neuro-Symbolic Losses

This repository holds the code for the AISTATS 2023 paper [Semantic Strengthening of Neuro-Symbolic Losses] by Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck

We introduce Semantic Strengthening,an approach for scalable neuro-symbolic learning. We approach the problem by first assuming the constraint decomposes conditioned on the features learned by the network. We iteratively strengthen our approximation, restoring the dependence between the constraints most responsible for degrading the quality of the approximation.


Installation

conda env create -f environment.yml

and if you encounter a pypsdd related error, running the following should solve the issue

pip install -vvv --upgrade --force-reinstall --no-binary :all: --no-deps pysdd

Commands

Each of the three tasks includes a .sh script.

Datasets

The Sudoku dataset can be found here: https://github.com/locuslab/SATNet

The MNIST Perfect Matching and Warcraft Shorest Path datasets can be found here: https://github.com/martius-lab/blackbox-differentiation-combinatorial-solvers

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