2 citations · 4 across the 5 of their papers we have counts for
4 papers
Trade-off between reconstruction loss and feature alignment for domain generalization
Thuan Nguyen, Boyang Lyu, Prakash Ishwar +2
Domain generalization (DG) is a branch of transfer learning that aims to train the learning models on several seen domains and subsequently apply these pre-trained models to other…
Geometric Sparse Coding in Wasserstein Space
Marshall Mueller, Shuchin Aeron, James M. Murphy +1
Wasserstein dictionary learning is an unsupervised approach to learning a collection of probability distributions that generate observed distributions as Wasserstein barycentric co…
Towards Designing and Exploiting Generative Networks for Neutrino Physics Experiments using Liquid Argon Time Projection Chambers
Paul Lutkus, Taritree Wongjirad, Shuchin Aeron
In this paper, we show that a hybrid approach to generative modeling via combining the decoder from an autoencoder together with an explicit generative model for the latent space i…
Robust and efficient change point detection using novel multivariate rank-energy GoF test
Shoaib Bin Masud, Shuchin Aeron
In this paper, we use and further develop upon a recently proposed multivariate, distribution-free Goodness-of-Fit (GoF) test based on the theory of Optimal Transport (OT) called t…