12 citations · 13 across the 4 of their papers we have counts for
4 papers
An Exact Kernel Equivalence for Finite Classification Models
Brian Bell, Michael Geyer, David Glickenstein +2
We explore the equivalence between neural networks and kernel methods by deriving the first exact representation of any finite-size parametric classification model trained with gra…
Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification
Kilian Zepf, Selma Wanna, Marco Miani +5
Image segmentation relies heavily on neural networks which are known to be overconfident, especially when making predictions on out-of-distribution (OOD) images. This is a common s…
Local Latent Space Bayesian Optimization over Structured Inputs
Natalie Maus, Haydn T. Jones, Juston S. Moore +3
Bayesian optimization over the latent spaces of deep autoencoder models (DAEs) has recently emerged as a promising new approach for optimizing challenging black-box functions over…
Inferring Multilateral Relations from Dynamic Pairwise Interactions
Aaron Schein, Juston Moore, Hanna Wallach
Correlations between anomalous activity patterns can yield pertinent information about complex social processes: a significant deviation from normal behavior, exhibited simultaneou…