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cs.LG2026
Learning to Bound: Monotonic, Calibrated Neural Upper Bounds for MPE Inference
Akshay Vyas, Hailiang Dong, Shivvrat Arya +4
Probabilistic graphical models (PGMs) compactly encode structured joint distributions, but Most Probable Explanation (MPE), which finds the highest-probability assignment to unobse…
cs.LG2026
A Novel Approach to Evaluating Evaluation Metrics for Multi-Output Structured Prediction
Akshay Vyas, Angelo Pimienta, Nicholas Ruozzi
In multi-output structured prediction tasks, while only one ground truth label may be provided in the training data, multiple equally valid outputs may be possible, making reliable…