4 papers
Fast Approximation of the Generalized Sliced-Wasserstein Distance
Dung Le, Huy Nguyen, Khai Nguyen +2
Generalized sliced Wasserstein distance is a variant of sliced Wasserstein distance that exploits the power of non-linear projection through a given defining function to better cap…
Structured Dropout Variational Inference for Bayesian Neural Networks
Son Nguyen, Duong Nguyen, Khai Nguyen +3
Approximate inference in Bayesian deep networks exhibits a dilemma of how to yield high fidelity posterior approximations while maintaining computational efficiency and scalability…
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein
Khai Nguyen, Son Nguyen, Nhat Ho +2
Relational regularized autoencoder (RAE) is a framework to learn the distribution of data by minimizing a reconstruction loss together with a relational regularization on the laten…
Distributional Sliced-Wasserstein and Applications to Generative Modeling
Khai Nguyen, Nhat Ho, Tung Pham +1
Sliced-Wasserstein distance (SW) and its variant, Max Sliced-Wasserstein distance (Max-SW), have been used widely in the recent years due to their fast computation and scalability…