18 citations · 41 across the 5 of their papers we have counts for
4 papers · 1 filter
A dictionary learning framework for graphs via filters and optimal transport
Jinchuan Liao, Dai Hai Nguyen
We propose a graph dictionary learning (GDL) framework where each graph is represented as a zero-mean Gaussian distribution derived from its filtered Laplacian. Each observed graph…
Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization
Dai Hai Nguyen, Duc Dung Nguyen, Atsuyoshi Nakamura +1
We study multi-objective optimization over probability distributions in Wasserstein space. Recently, Nguyen et al. (2025) introduced Multiple Wasserstein Gradient Descent (MWGraD)…
On a linear fused Gromov-Wasserstein distance for graph structured data
Dai Hai Nguyen, Koji Tsuda
We present a framework for embedding graph structured data into a vector space, taking into account node features and topology of a graph into the optimal transport (OT) problem. T…
Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
Graph is an usual representation of relational data, which are ubiquitous in manydomains such as molecules, biological and social networks. A popular approach to learningwith graph…