67 citations · 238 across the 29 of their papers we have counts for
4 papers · 1 filter
Using Deep Image Priors to Generate Counterfactual Explanations
Vivek Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias
Through the use of carefully tailored convolutional neural network architectures, a deep image prior (DIP) can be used to obtain pre-images from latent representation encodings. Th…
Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks
Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias
Graph Neural Networks (GNNs), a generalization of neural networks to graph-structured data, are often implemented using message passes between entities of a graph. While GNNs are e…
Accurate and Robust Feature Importance Estimation under Distribution Shifts
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Rushil Anirudh +2
With increasing reliance on the outcomes of black-box models in critical applications, post-hoc explainability tools that do not require access to the model internals are often use…
Unsupervised Audio Source Separation using Generative Priors
Vivek Narayanaswamy, Jayaraman J. Thiagarajan, Rushil Anirudh +1
State-of-the-art under-determined audio source separation systems rely on supervised end-end training of carefully tailored neural network architectures operating either in the tim…