31 citations · 32 across the 5 of their papers we have counts for
5 papers
A New Look at the Ensemble Kalman Filter for Inverse Problems: Duality, Non-Asymptotic Analysis and Convergence Acceleration
C G Krishnanunni, Jonathan Wittmer, Tan Bui-Thanh +1
This work presents new results and understanding of the Ensemble Kalman filter (EnKF) for inverse problems. In particular, using a Lagrangian dual perspective we show that EnKF can…
Aria Gen 2 Pilot Dataset
Chen Kong, James Fort, Aria Kang +20
The Aria Gen 2 Pilot Dataset (A2PD) is an egocentric multimodal open dataset captured using the state-of-the-art Aria Gen 2 glasses. To facilitate timely access, A2PD is released i…
An autoencoder compression approach for accelerating large-scale inverse problems
Jonathan Wittmer, Jacob Badger, Hari Sundar +1
PDE-constrained inverse problems are some of the most challenging and computationally demanding problems in computational science today. Fine meshes that are required to accurately…
On Unifying Randomized Methods For Inverse Problems
Jonathan Wittmer, C. G. Krishnanunni, Hai V. Nguyen +1
This work unifies the analysis of various randomized methods for solving linear and nonlinear inverse problems by framing the problem in a stochastic optimization setting. By doing…
Solving Bayesian Inverse Problems via Variational Autoencoders
Hwan Goh, Sheroze Sheriffdeen, Jonathan Wittmer +1
In recent years, the field of machine learning has made phenomenal progress in the pursuit of simulating real-world data generation processes. One notable example of such success i…