Emory

MATH 789R - Reading Seminar on Mathematics of Machine Learning

In this seminar, we discuss one recent work at the interface of applied mathematics and machine learning with the goal of exposing new research questions.

CS 584 - Numerical Methods for Deep Learning

This course provides students with the mathematical background needed to analyze and further develop numerical methods at the heart of deep learning.

MATH 347 - Introduction to Nonlinear Optimization

This advanced undergraduate course introduces nonlinear optimization problems, optimality conditions, and examples from different domains including finance, machine learning, and imaging.

MATH 516 - Numerical Analysis II

This course, which is part two of our three-part graduate sequence on numerical analysis, focusses on optimization, root finding, interpolation, differentiation, integration, and differential equations.

MATH 571 - Numerical Optimization

This course provides students with an overview of state-of-the-art numerical methods for solving both unconstrained and constrained, large-scale optimization problems.

MATH 315 - Numerical Analysis

This undergraduate course provides an introduction to numerical methods (linear systems, data fitting, differentiation, integration, root finding, and minimization) and scientific computing using MATLAB.

MATH 789R - Bayesian Inverse Problems and Uncertainty Quantification

This special topics course introduces basic concepts as well as more recent advances in Bayesian methods for solving inverse problems.

MATH 211 - Multivariable Calculus

Third part of our standard calculus sequence.

MATH 346 - Introduction to Optimization Theory

This undergraduate course provides the fundamental theory for optimization problems (linear, quadratic, nonlinear, combinatorial).