ML models are increasingly being pushed to mobile devices, for low-laten...
In this paper, we consider inference in the context of a factor model fo...
Factor models have been widely used in economics and finance. However, t...
We present a discretization-free scalable framework for solving a large ...
Few-shot image generation is a challenging task since it aims to generat...
Sampling from a target measure whose density is only known up to a
norma...
Tensor Factor Models (TFM) are appealing dimension reduction tools for
h...
Wasserstein barycenters have become popular due to their ability to repr...
Finding multiple solutions of non-convex optimization problems is a
ubiq...
A new conservative finite element solver for the three-dimensional stead...
Efficient and robust iterative solvers for strong anisotropic elliptic
e...
Standard PolyCube-based hexahedral (hex) meshing methods aim to deform t...
Despite the recent popularity of neural network-based solvers for optima...
Wasserstein gradient flows provide a powerful means of understanding and...
Wasserstein barycenters provide a geometric notion of the weighted avera...
Wasserstein barycenters provide a geometrically meaningful way to aggreg...
In this paper we study finite element method for three-dimensional
incom...
Due to the popularity of smartphones, cheap wireless networks and
availa...
Pair-based metric learning has been widely adopted to learn sentence
emb...
Fitting geometric primitives to 3D point cloud data bridges a gap betwee...