130 citations · 309 across the 8 of their papers we have counts for
8 papers
Learning Partially Observable Deterministic Action Models
Eyal Amir, Allen Chang
We present exact algorithms for identifying deterministic-actions effects and preconditions in dynamic partially observable domains. They apply when one does not know the action mo…
Efficient Approximation for Triangulation of Minimum Treewidth
Eyal Amir
We present four novel approximation algorithms for finding triangulation of minimum treewidth. Two of the algorithms improve on the running times of algorithms by Robertson and Sey…
Lifted Relational Variational Inference
Jaesik Choi, Eyal Amir
Hybrid continuous-discrete models naturally represent many real-world applications in robotics, finance, and environmental engineering. Inference with large-scale models is challen…
Reachability Under Uncertainty
Allen Chang, Eyal Amir
In this paper we introduce a new network reachability problem where the goal is to find the most reliable path between two nodes in a network, represented as a directed acyclic gra…
Sampling First Order Logical Particles
Hannaneh Hajishirzi, Eyal Amir
Approximate inference in dynamic systems is the problem of estimating the state of the system given a sequence of actions and partial observations. High precision estimation is fun…
Lifted Inference for Relational Continuous Models
Jaesik Choi, Eyal Amir, David J. Hill
Relational Continuous Models (RCMs) represent joint probability densities over attributes of objects, when the attributes have continuous domains. With relational representations,…