5 papers
Spherical Tree-Sliced Wasserstein Distance
Viet-Hoang Tran, Thanh T. Chu, Khoi N. M. Nguyen +3
Sliced Optimal Transport (OT) simplifies the OT problem in high-dimensional spaces by projecting supports of input measures onto one-dimensional lines and then exploiting the close…
Distance-Based Tree-Sliced Wasserstein Distance
Hoang V. Tran, Khoi N. M. Nguyen, Trang Pham +3
To overcome computational challenges of Optimal Transport (OT), several variants of Sliced Wasserstein (SW) has been developed in the literature. These approaches exploit the close…
A Clifford Algebraic Approach to E(n)-Equivariant High-order Graph Neural Networks
Viet-Hoang Tran, Thieu N. Vo, Tho Tran Huu +1
Designing neural network architectures that can handle data symmetry is crucial. This is especially important for geometric graphs whose properties are equivariance under Euclidean…
Monomial Matrix Group Equivariant Neural Functional Networks
Viet-Hoang Tran, Thieu N. Vo, Tho H. Tran +2
Neural functional networks (NFNs) have recently gained significant attention due to their diverse applications, ranging from predicting network generalization and network editing t…
Tree-Sliced Wasserstein Distance: A Geometric Perspective
Viet-Hoang Tran, Trang Pham, Tho Tran +4
Many variants of Optimal Transport (OT) have been developed to address its heavy computation. Among them, notably, Sliced Wasserstein (SW) is widely used for application domains by…