Deep Learning: Is it the Answer to Artificial Intelligence?


November 30, 2018 | 2:30 - 3:30 p.m.


Campbell Hall 443


Prof. Nidhal Bouaynaya, Rowan University


Within the field of machine learning, deep learning approaches have resulted in state-of-the-art accuracy in visual object detection, speech recognition, and many other domains including genomics. Deep learning techniques hold the promise of emerging technologies, such as autonomous unmanned vehicles, smart cities infrastructure, personalized treatment in medicine, and cybersecurity. However, deep learning models are deterministic, and as a result are unable to understand or assess their uncertainty, a critical part of any predictive system’s output. This can have disastrous consequences, especially when the output of such models is fed into higher-level decision making procedures, such as medical diagnosis or autonomous vehicles. This talk is divided into two parts. First, we provide intuitive insights into deep learning models and show their applications in healthcare and aviation. We then introduce Bayesian deep learning to assess the model’s confidence in its prediction and show preliminary results on robustness to noise and artifacts in the data as well as resilience to adversarial attacks.