102 citations · 251 across the 16 of their papers we have counts for
3 papers · 1 filter
Approximate blocked Gibbs sampling for Bayesian neural networks
Theodore Papamarkou
In this work, minibatch MCMC sampling for feedforward neural networks is made more feasible. To this end, it is proposed to sample subgroups of parameters via a blocked Gibbs sampl…
Topological Deep Learning: Going Beyond Graph Data
Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou +11
Topological deep learning is a rapidly growing field that pertains to the development of deep learning models for data supported on topological domains such as simplicial complexes…
The Inverse Problem for Single Trajectories of Rough Differential Equations
Thomas Morrish, Theodore Papamarkou, Anastasia Papavasiliou +1
Motivated by the need to develop a general framework for performing statistical inference for discretely observed random rough differential equations, our aim is to construct a geo…