Arithmetic Circuit

Arithmetic circuits are computational structures representing computations as directed acyclic graphs, offering a framework for efficient and tractable computations in various fields. Current research focuses on developing and analyzing different arithmetic circuit architectures, such as probabilistic circuits (including sum-of-squares variants) and their application in areas like probabilistic machine learning, causal inference, and robotic motion planning. These circuits are proving valuable for improving the efficiency and explainability of algorithms, particularly in scenarios where traditional methods face computational bottlenecks or lack interpretability, with applications ranging from faster private machine learning inference to more efficient solutions for complex optimization problems.