CSCI 8350 Deep Learning

The course aims to (i) introduce important recent advances in deep learning models, such as deep reinforcement learning, Generative Adversarial Networks, recurrent neural networks, graph neural networks, and interpretation of neural networks, and (ii) apply and develop new algorithms for student research. It is required that students had previously taken Intro to Deep Learning, prior to this one. The course consists of: (i) studying state-of-the-art architectural and modeling concepts, (ii)  reviewing recent literature and reproducing the results with applications of interest to students, (iii) developing innovative ideas for a research problem students pursue, (iv) presenting proposal students made (v) delivering a final presentation and research paper.

Credits

3

Prerequisite

Consent of instructor.

Schedule Type

Lecture

Grading Basis

Standard Letter (A-F)

Administrative Unit

Computer Science

Offered

As Scheduled