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Found 7 papers, 2 papers with code
Continual Reinforcement Learning with TELLA
Training reinforcement learning agents that continually learn across multiple environments is a challenging problem.
Addressing Visual Search in Open and Closed Set Settings
We interpret both detection problems through a probabilistic, Bayesian lens, whereby the objectness maps produced by our method serve as priors in a maximum-a-posteriori approach to the detection step.
Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis
We present a technique that utilizes properties of random projections to characterize the behavior of clean and adversarial examples across a diverse set of subspaces.
Jacks of All Trades, Masters Of None: Addressing Distributional Shift and Obtrusiveness via Transparent Patch Attacks
We focus on the development of effective adversarial patch attacks and -- for the first time -- jointly address the antagonistic objectives of attack success and obtrusiveness via the design of novel semi-transparent patches.
The TrojAI Software Framework: An OpenSource tool for Embedding Trojans into Deep Learning Models
In this paper, we introduce the TrojAI software framework, an open source set of Python tools capable of generating triggered (poisoned) datasets and associated deep learning (DL) models with trojans at scale.
Adversarial Examples in Remote Sensing
This paper considers attacks against machine learning algorithms used in remote sensing applications, a domain that presents a suite of challenges that are not fully addressed by current research focused on natural image data such as ImageNet.
Functional Map of the World
We present an analysis of the dataset along with baseline approaches that reason about metadata and temporal views.
