Math 640: EXPERIMENTAL MATHEMATICS (Combinatorial Deep Learning) (Spring 2027)

http://sites.math.rutgers.edu/~zeilberg/math640_26.html

Last Update: Oct. 11, 2026


Description

Experimental Mathematics used to be considered an oxymoron, but the future of mathematics is in that direction. In addition to learning the philosophy and methodology of this budding field, students will become computer-algebra wizards, and that should be very helpful in whatever mathematical specialty they are doing (or will do) research in.

We will first learn Maple, and how to program with it. This semester we will learn, from an experimental mathematics and symbolic-computation point of view, Combinatorial Deep Learning and Bayesian methods.

The final projects may lead to published papers. People who already took previous editions of this class are welcome to take it again, since except for the basics, there is very little overlap with previous years.

This class is suitable for graduate students in other departments, and the software development skills learned will be useful for doing any quantitative research. Very smart advanced undergraduates are also welcome.



Optional (but Highly recommended) Getting Started Homework

Teach yourself the basics of Maple by reading Frank Garvan's golden-oldie part 1, part 2
Note: a few commands are no longer valid in today's Maple. The most important one is that " has been replaced by %.

For more details, see this 2002 masterpiece.

How to submit homework


Dr. Z.'s teaching page