1 citations · 2 across the 5 of their papers we have counts for
3 papers · 1 filter
On the Versatile Uses of Partial Distance Correlation in Deep Learning
Xingjian Zhen, Zihang Meng, Rudrasis Chakraborty +1
Comparing the functional behavior of neural network models, whether it is a single network over time or two (or more networks) during or post-training, is an essential step in unde…
Deep Unlearning via Randomized Conditionally Independent Hessians
Ronak Mehta, Sourav Pal, Vikas Singh +1
Recent legislation has led to interest in machine unlearning, i.e., removing specific training samples from a predictive model as if they never existed in the training dataset. Unl…
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators
Zihang Meng, Vikas Singh, Sathya N. Ravi
We study how stochastic differential equation (SDE) based ideas can inspire new modifications to existing algorithms for a set of problems in computer vision. Loosely speaking, our…