Search Results for author:
Found 4 papers, 1 papers with code
Finding path and cycle counting formulae in graphs with Deep Reinforcement Learning
This paper presents Grammar Reinforcement Learning (GRL), a reinforcement learning algorithm that uses Monte Carlo Tree Search (MCTS) and a transformer architecture that models a Pushdown Automaton (PDA) within a context-free grammar (CFG) framework.
Technical report: Graph Neural Networks go Grammatical
This paper introduces a framework for formally establishing a connection between a portion of an algebraic language and a Graph Neural Network (GNN).
Theoretical Guarantees for Bridging Metric Measure Embedding and Optimal Transport
Unlike Gromov-Wasserstein (GW) distance which compares pairwise distances of elements from each distribution, we consider a method allowing to embed the metric measure spaces in a common Euclidean space and compute an optimal transport (OT) on the embedded distributions.
Screening Sinkhorn Algorithm for Regularized Optimal Transport
We introduce in this paper a novel strategy for efficiently approximating the Sinkhorn distance between two discrete measures.
