1 citations · 2 across the 4 of their papers we have counts for
4 papers
Investigating the Impact of Weight Sharing Decisions on Knowledge Transfer in Continual Learning
Josh Andle, Ali Payani, Salimeh Yasaei-Sekeh
Continual Learning (CL) has generated attention as a method of avoiding Catastrophic Forgetting (CF) in the sequential training of neural networks, improving network efficiency and…
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness
Jovon Craig, Josh Andle, Theodore S. Nowak +1
The robustness of deep neural networks (DNNs) against adversarial attacks has been studied extensively in hopes of both better understanding how deep learning models converge and i…
Theoretical Understanding of the Information Flow on Continual Learning Performance
Josh Andle, Salimeh Yasaei Sekeh
Continual learning (CL) is a setting in which an agent has to learn from an incoming stream of data sequentially. CL performance evaluates the model's ability to continually learn…
The Stanford Drone Dataset is More Complex than We Think: An Analysis of Key Characteristics
Joshua Andle, Nicholas Soucy, Simon Socolow +1
Several datasets exist which contain annotated information of individuals' trajectories. Such datasets are vital for many real-world applications, including trajectory prediction a…