3 papers
cs.AI2026
Learning to Guide Local Search for MPE Inference in Probabilistic Graphical Models
Brij Malhotra, Shivvrat Arya, Tahrima Rahman +1
Most Probable Explanation (MPE) inference in Probabilistic Graphical Models (PGMs) is a fundamental yet computationally challenging problem arising in domains such as diagnosis, pl…
cs.LG2025
Learning to Condition: A Neural Heuristic for Scalable MPE Inference
Brij Malhotra, Shivvrat Arya, Tahrima Rahman +1
We introduce learning to condition (L2C), a scalable, data-driven framework for accelerating Most Probable Explanation (MPE) inference in Probabilistic Graphical Models (PGMs), a f…
cs.CV2024
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities
Rohith Peddi, Shivvrat Arya, Bharath Challa +10
Following step-by-step procedures is an essential component of various activities carried out by individuals in their daily lives. These procedures serve as a guiding framework tha…