1 citations · 1 across the 1 of their papers we have counts for
4 papers
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…
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…
The Efficiency of Geometric Samplers for Exoplanet Transit Timing Variation Models
Noah W. Tuchow, Eric B. Ford, Theodore Papamarkou +1
Transit timing variations (TTVs) are a valuable tool to determine the masses and orbits of transiting planets in multi-planet systems. TTVs can be readily modeled given knowledge o…