research
∙
05/26/2023
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence
Despite the progress in deep learning networks, efficient learning at th...
share
research
∙
08/19/2022
A Risk-Sensitive Approach to Policy Optimization
Standard deep reinforcement learning (DRL) aims to maximize expected rew...
research
∙
04/06/2021
Out-of-Distribution Robustness with Deep Recursive Filters
Accurate state and uncertainty estimation is imperative for mobile robot...
research
∙
05/01/2020
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 –...
research
∙
02/25/2020
TanksWorld: A Multi-Agent Environment for AI Safety Research
The ability to create artificial intelligence (AI) capable of performing...
research
∙
02/25/2020
Unsupervised Semantic Attribute Discovery and Control in Generative Models
This work focuses on the ability to control via latent space factors sem...
research
∙
05/28/2018
Adversarial Examples in Remote Sensing
This paper considers attacks against machine learning algorithms used in...
research
∙
12/08/2017
Combining Deep Universal Features, Semantic Attributes, and Hierarchical Classification for Zero-Shot Learning
We address zero-shot (ZS) learning, building upon prior work in hierarch...
research
∙
06/24/2014
Techniques for clustering interaction data as a collection of graphs
A natural approach to analyze interaction data of form "what-connects-to...
research
∙
06/24/2014