37 citations · 44 across the 3 of their papers we have counts for
3 papers
Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features
Ibrahima Ndiour, Nilesh Ahuja, Omesh Tickoo
This paper presents a principled approach for detecting out-of-distribution (OOD) samples in deep neural networks (DNN). Modeling probability distributions on deep features has rec…
Deep Probabilistic Models to Detect Data Poisoning Attacks
Mahesh Subedar, Nilesh Ahuja, Ranganath Krishnan +2
Data poisoning attacks compromise the integrity of machine-learning models by introducing malicious training samples to influence the results during test time. In this work, we inv…
Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection
Nilesh A. Ahuja, Ibrahima Ndiour, Trushant Kalyanpur +1
We present a principled approach for detecting out-of-distribution (OOD) and adversarial samples in deep neural networks. Our approach consists in modeling the outputs of the vario…