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Found 3 papers, 1 papers with code
Engineering an Exact Pseudo-Boolean Model Counter
Our work opens up several avenues for future work in the context of model counting for PB formulas, such as the development of preprocessing techniques and exploration of approaches other than knowledge compilation.
Scalable Probabilistic Routes
In this work, our contributions are two-fold: first, we introduce a relaxed encoding that uses a linear number of variables with respect to the number of vertices in a road network graph to significantly reduce the size of resultant decision diagrams.
Predicting Forest Fire Using Remote Sensing Data And Machine Learning
The results support our claim that machine-learning based approaches can lead to reliable and cost-effective forest fire prediction systems.
