11 citations · 11 across the 4 of their papers we have counts for
6 papers · 1 filter
INDIGO: Intrinsic Multimodality for Domain Generalization
Puneet Mangla, Shivam Chandhok, Milan Aggarwal +2
For models to generalize under unseen domains (a.k.a domain generalization), it is crucial to learn feature representations that are domain-agnostic and capture the underlying sema…
Context-Conditional Adaptation for Recognizing Unseen Classes in Unseen Domains
Puneet Mangla, Shivam Chandhok, Vineeth N Balasubramanian +1
Recent progress towards designing models that can generalize to unseen domains (i.e domain generalization) or unseen classes (i.e zero-shot learning) has embarked interest towards…
Data InStance Prior (DISP) in Generative Adversarial Networks
Puneet Mangla, Nupur Kumari, Mayank Singh +2
Recent advances in generative adversarial networks (GANs) have shown remarkable progress in generating high-quality images. However, this gain in performance depends on the availab…
On Saliency Maps and Adversarial Robustness
Puneet Mangla, Vedant Singh, Vineeth N Balasubramanian
A Very recent trend has emerged to couple the notion of interpretability and adversarial robustness, unlike earlier efforts which solely focused on good interpretations or robustne…
Attributional Robustness Training using Input-Gradient Spatial Alignment
Mayank Singh, Nupur Kumari, Puneet Mangla +3
Interpretability is an emerging area of research in trustworthy machine learning. Safe deployment of machine learning system mandates that the prediction and its explanation be rel…
AdvGAN++ : Harnessing latent layers for adversary generation
Puneet Mangla, Surgan Jandial, Sakshi Varshney +1
Adversarial examples are fabricated examples, indistinguishable from the original image that mislead neural networks and drastically lower their performance. Recently proposed AdvG…