most citedEnsemble estimation of multivariate f-divergence

59 citations · 98 across the 3 of their papers we have counts for

collaborators

7 papers

stat.ML20241 cited

Training-Free Guidance for Discrete Diffusion Models for Molecular Generation

Thomas J. Kerby, Kevin R. Moon

Training-free guidance methods for continuous data have seen an explosion of interest due to the fact that they enable foundation diffusion models to be paired with interchangable…

cs.LG2024

Incorporating Taylor Series and Recursive Structure in Neural Networks for Time Series Prediction

Jarrod Mau, Kevin Moon

Time series analysis is relevant in various disciplines such as physics, biology, chemistry, and finance. In this paper, we present a novel neural network architecture that integra…

cs.LG2024

Exploring higher-order neural network node interactions with total correlation

Thomas Kerby, Teresa White, Kevin Moon

In domains such as ecological systems, collaborations, and the human brain the variables interact in complex ways. Yet accurately characterizing higher-order variable interactions…

cs.CV2024

Local Background Estimation for Improved Gas Plume Identification in Hyperspectral Images

Scout Jarman, Zigfried Hampel-Arias, Adra Carr +1

Deep learning identification models have shown promise for identifying gas plumes in Longwave IR hyperspectral images of urban scenes, particularly when a large library of gases ar…

cs.IT201429 cited

Multivariate f-Divergence Estimation With Confidence

Kevin R. Moon, Alfred O. Hero

The problem of f-divergence estimation is important in the fields of machine learning, information theory, and statistics. While several nonparametric divergence estimators exist,…

cs.CV201410 cited

Image patch analysis and clustering of sunspots: a dimensionality reduction approach

Kevin R. Moon, Jimmy J. Li, Veronique Delouille +2

Sunspots, as seen in white light or continuum images, are associated with regions of high magnetic activity on the Sun, visible on magnetogram images. Their complexity is correlate…