2 citations · 2 across the 5 of their papers we have counts for
5 papers
An optimal control approach for neural network architecture adaptation with a posteriori error estimation
C G Krishnanunni, Thomas Scott, Tan Bui-Thanh
This work presents a novel approach for adapting neural network architecture along the depth based on a posteriori error estimation. By formulating neural network training as a con…
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…
Topological derivative approach for deep neural network architecture adaptation
C G Krishnanunni, Tan Bui-Thanh, Clint Dawson
This work presents a novel algorithm for progressively adapting neural network architecture along the depth. In particular, we attempt to address the following questions in a mathe…
LiLaN: A Linear Latent Network as the Solution Operator for Real-Time Solutions to Stiff Nonlinear Ordinary Differential Equations
William Cole Nockolds, C. G. Krishnanunni, Tan Bui-Thanh +1
Solving stiff ordinary differential equations (StODEs) requires sophisticated numerical solvers, which are often computationally expensive. In general, traditional explicit time in…
An Adaptive and Stability-Promoting Layerwise Training Approach for Sparse Deep Neural Network Architecture
C G Krishnanunni, Tan Bui-Thanh
This work presents a two-stage adaptive framework for progressively developing deep neural network (DNN) architectures that generalize well for a given training data set. In the fi…