1 citations · 1 across the 4 of their papers we have counts for
4 papers
Error-Conditioned Neural Solvers
Haina Jiang, Liam Wang, Peng-Chen Chen +4
Neural surrogate models offer fast approximate mappings from PDE parameters to solutions, but they typically treat solving as a purely statistical task: once trained, they struggle…
Efficient Analysis of the Distilled Neural Tangent Kernel
Jamie Mahowald, Brian Bell, Alex Ho +1
Neural tangent kernel (NTK) methods are computationally limited by the need to evaluate large Jacobians across many data points. Existing approaches reduce this cost primarily thro…
Persistent Classification: A New Approach to Stability of Data and Adversarial Examples
Brian Bell, Michael Geyer, David Glickenstein +4
There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high-dimensionality of the data, high codimension i…
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…