31 citations · 86 across the 12 of their papers we have counts for
6 papers · 1 filter
ChemTime: Rapid and Early Classification for Multivariate Time Series Classification of Chemical Sensors
Alexander M. Moore, Randy C. Paffenroth, Kenneth T. Ngo +1
Multivariate time series data are ubiquitous in the application of machine learning to problems in the physical sciences. Chemiresistive sensor arrays are highly promising in chemi…
ChemVise: Maximizing Out-of-Distribution Chemical Detection with the Novel Application of Zero-Shot Learning
Alexander M. Moore, Randy C. Paffenroth, Ken T. Ngo +1
Accurate chemical sensors are vital in medical, military, and home safety applications. Training machine learning models to be accurate on real world chemical sensor data requires…
Reconstruction of Fragmented Trajectories of Collective Motion using Hadamard Deep Autoencoders
Kelum Gajamannage, Yonggi Park, Randy Paffenroth +1
Learning dynamics of collectively moving agents such as fish or humans is an active field in research. Due to natural phenomena such as occlusion and change of illumination, the mu…
Neural Network Ensembles: Theory, Training, and the Importance of Explicit Diversity
Wenjing Li, Randy C. Paffenroth, David Berthiaume
Ensemble learning is a process by which multiple base learners are strategically generated and combined into one composite learner. There are two features that are essential to an…
Bounded Manifold Completion
Kelum Gajamannage, Randy Paffenroth
Nonlinear dimensionality reduction or, equivalently, the approximation of high-dimensional data using a low-dimensional nonlinear manifold is an active area of research. In this pa…
Dimension Estimation Using Autoencoders
Nitish Bahadur, Randy Paffenroth
Dimension Estimation (DE) and Dimension Reduction (DR) are two closely related topics, but with quite different goals. In DE, one attempts to estimate the intrinsic dimensionality…