20 citations · 43 across the 9 of their papers we have counts for
3 papers · 1 filter
Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey
Abdelwahed Khamis, Russell Tsuchida, Mohamed Tarek +2
Optimal Transport (OT) is a mathematical framework that first emerged in the eighteenth century and has led to a plethora of methods for answering many theoretical and applied ques…
Bayesian Neural Ordinary Differential Equations
Raj Dandekar, Karen Chung, Vaibhav Dixit +4
Recently, Neural Ordinary Differential Equations has emerged as a powerful framework for modeling physical simulations without explicitly defining the ODEs governing the system, bu…
DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models
Mohamed Tarek, Kai Xu, Martin Trapp +2
We present the preliminary high-level design and features of DynamicPPL.jl, a modular library providing a lightning-fast infrastructure for probabilistic programming. Besides a com…