This paper presents a novel deep learning approach for analyzing massive...
This paper investigates the relationship between the universal approxima...
Neural networks are often biased to spuriously correlated features that
...
To understand learning the dynamics of deep ReLU networks, we investigat...
Using publicly accessible maps, we propose a novel vehicle localization
...
Understanding implicit bias of gradient descent has been an important go...
End-to-end approaches open a new way for more accurate and efficient spo...
As an emerging field in Machine Learning, Explainable AI (XAI) has been
...
In this paper, we propose a novel abnormal event detection method with
s...
In this paper, we propose Dynamics Transfer GAN; a new method for genera...
We present Mantis, a new framework that automatically predicts program
p...