102 citations · 251 across the 16 of their papers we have counts for
5 papers · 1 filter
Inferring the spread of COVID-19: the role of time-varying reporting rate in epidemiological modelling
Adam Spannaus, Theodore Papamarkou, Samantha Erwin +1
The role of epidemiological models is crucial for informing public health officials during a public health emergency, such as the COVID-19 pandemic. However, traditional epidemiolo…
Bayesian neural networks and dimensionality reduction
Deborshee Sen, Theodore Papamarkou, David Dunson
In conducting non-linear dimensionality reduction and feature learning, it is common to suppose that the data lie near a lower-dimensional manifold. A class of model-based approach…
Hidden Markov models as recurrent neural networks: an application to Alzheimer's disease
Matt Baucum, Anahita Khojandi, Theodore Papamarkou
Hidden Markov models (HMMs) are commonly used for disease progression modeling when the true patient health state is not fully known. Since HMMs typically have multiple local optim…
Automated detection of corrosion in used nuclear fuel dry storage canisters using residual neural networks
Theodore Papamarkou, Hayley Guy, Bryce Kroencke +8
Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability…
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes
Devanshu Agrawal, Theodore Papamarkou, Jacob Hinkle
There has recently been much work on the "wide limit" of neural networks, where Bayesian neural networks (BNNs) are shown to converge to a Gaussian process (GP) as all hidden layer…