📚 Methods Implemented in NeuPI

🔹 Single-Pass Inference & Marginal MAP in Probabilistic Circuits

Arya, Shivvrat, Rahman, Tahrima, and Gogate, Vibhav. “Neural Network Approximators for Marginal MAP in Probabilistic Circuits.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 10, 2024, pp. 10918–10926. https://doi.org/10.1609/aaai.v38i10.28966

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🔹 Single-Pass Inference & Neural Embeddings for Constrained MPE

Arya, Shivvrat, Rahman, Tahrima, and Gogate, Vibhav. “Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models.” Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2024, pp. 2791–2799.

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🔹 ITSELF Engine for General MPE Inference

Arya, Shivvrat, Rahman, Tahrima, and Gogate, Vibhav Giridhar. “A Neural Network Approach for Efficiently Answering Most Probable Explanation Queries in Probabilistic Models.” Thirty-eighth Conference on Neural Information Processing Systems (NeurIPS), 2024.

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🔹 SINE: Enhanced Neural Embeddings and Discretization for Probabilistic Graphical Models

Arya, Shivvrat, Rahman, Tahrima, and Gogate, Vibhav Giridhar. “SINE: Scalable MPE Inference for Probabilistic Graphical Models Using Advanced Neural Embeddings.” Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025.