3 citations · 4 across the 4 of their papers we have counts for
5 papers
Class Density and Dataset Quality in High-Dimensional, Unstructured Data
Adam Byerly, Tatiana Kalganova
We provide a definition for class density that can be used to measure the aggregate similarity of the samples within each of the classes in a high-dimensional, unstructured dataset…
Towards an Analytical Definition of Sufficient Data
Adam Byerly, Tatiana Kalganova
We show that, for each of five datasets of increasing complexity, certain training samples are more informative of class membership than others. These samples can be identified a p…
On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of micro-PCBs
Adam Byerly, Tatiana Kalganova, Anthony J. Grichnik
We present a dataset consisting of high-resolution images of 13 micro-PCBs captured in various rotations and perspectives relative to the camera, with each sample labeled for PCB t…
No Routing Needed Between Capsules
Adam Byerly, Tatiana Kalganova, Ian Dear
Most capsule network designs rely on traditional matrix multiplication between capsule layers and computationally expensive routing mechanisms to deal with the capsule dimensional…
Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks
Adam Byerly, Tatiana Kalganova
Capsules are the name given by Geoffrey Hinton to vector-valued neurons. Neural networks traditionally produce a scalar value for an activated neuron. Capsules, on the other hand,…