Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We
propose that to accelerate progress in AI, we must invest in fundamental research in …

Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …

Nowadays, deep neural networks are widely used in mission critical systems such as
healthcare, self-driving vehicles, and military which have direct impact on human lives …

Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …

ABSTRACT The Internet of Things (IoT) is a relatively new technology that has piqued
academics' and business information systems' attention in recent years. The Internet of …

Deep neural networks (DNN) have achieved unprecedented success in numerous machine
learning tasks in various domains. However, the existence of adversarial examples raises …

We identify a trade-off between robustness and accuracy that serves as a guiding principle
in the design of defenses against adversarial examples. Although this problem has been …

With the rapid developments of artificial intelligence (AI) and deep learning (DL) techniques,
it is critical to ensure the security and robustness of the deployed algorithms. Recently, the …

Generative adversarial network (GANs) is one of the most important research avenues in the
field of artificial intelligence, and its outstanding data generation capacity has received wide …

A deep reinforcement learning (DRL) agent observes its states through observations, which
may contain natural measurement errors or adversarial noises. Since the observations …