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Found 2 papers, 1 papers with code
Goal Agnostic Planning using Maximum Likelihood Paths in Hypergraph World Models
In this paper, we present a hypergraph--based machine learning algorithm, a datastructure--driven maintenance method, and a planning algorithm based on a probabilistic application of Dijkstra's algorithm.
Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
Learning models with discrete latent variables using stochastic gradient descent remains a challenge due to the high variance of gradient estimates.
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