Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection

no code implementations • 20 Mar 2022 • Ibrahima J. Ndiour, Nilesh A. Ahuja, Omesh Tickoo

This paper presents a fast, principled approach for detecting anomalous and out-of-distribution (OOD) samples in deep neural networks (DNN).

Anomaly Detection Dimensionality Reduction

Deep Probabilistic Models to Detect Data Poisoning Attacks

no code implementations • 3 Dec 2019 • Mahesh Subedar, Nilesh Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo

In the second approach, we use Bayesian deep neural networks trained with mean-field variational inference to estimate model uncertainty associated with the predictions.

Data Poisoning Variational Inference