most citedIB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

math.NA2023★ 2 cited

IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning

Ling Guo, Hao Wu, Wenwen Zhou +2

We propose a novel framework for uncertainty quantification via information bottleneck (IB-UQ) for scientific machine learning tasks, including deep neural network (DNN) regression…

math.OC2022

A Novel Fast Exact Subproblem Solver for Stochastic Quasi-Newton Cubic Regularized Optimization

Jarad Forristal, Joshua Griffin, Wenwen Zhou +1

In this work we describe an Adaptive Regularization using Cubics (ARC) method for large-scale nonconvex unconstrained optimization using Limited-memory Quasi-Newton (LQN) matrices.…