Search Results for author:
Found 6 papers, 3 papers with code
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
In this regard, previous WGF models employ the JKO scheme and parametrize transport map for each JKO step.
Analyzing and Improving Optimal-Transport-based Adversarial Networks
In this paper, we begin by unifying these OT-based adversarial methods within a single framework.
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport
In this paper, we propose a novel generative model based on the semi-dual formulation of Unbalanced Optimal Transport (UOT).
Restoration based Generative Models
Also, we propose a multi-scale training, which improves the performance compared to the diffusion process, by taking advantage of the flexibility of the forward process.
Learning PDE Solution Operator for Continuous Modeling of Time-Series
Learning underlying dynamics from data is important and challenging in many real-world scenarios.
Robust Out-of-Distribution Detection on Deep Probabilistic Generative Models
Deep probabilistic generative models facilitate OOD detection by estimating the likelihood of a data sample.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
