289 citations · 1.2k across the 72 of their papers we have counts for
5 papers · 1 filter
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification
Ruoxi Jiang, Rebecca Willett
This paper explores learning emulators for parameter estimation with uncertainty estimation of high-dimensional dynamical systems. We assume access to a computationally complex sim…
Cloud Classification with Unsupervised Deep Learning
Takuya Kurihana, Ian Foster, Rebecca Willett +6
We present a framework for cloud characterization that leverages modern unsupervised deep learning technologies. While previous neural network-based cloud classification models hav…
Lazy Estimation of Variable Importance for Large Neural Networks
Yue Gao, Abby Stevens, Rebecca Willet +1
As opaque predictive models increasingly impact many areas of modern life, interest in quantifying the importance of a given input variable for making a specific prediction has gro…
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction
Yi Ding, Avinash Rao, Hyebin Song +2
Datacenters execute large computational jobs, which are composed of smaller tasks. A job completes when all its tasks finish, so stragglers -- rare, yet extremely slow tasks -- are…
The Role of Linear Layers in Nonlinear Interpolating Networks
Greg Ongie, Rebecca Willett
This paper explores the implicit bias of overparameterized neural networks of depth greater than two layers. Our framework considers a family of networks of varying depth that all…