Parallel Computing and Scientific Machine Learning

Mixing Differential Equations and Neural Networks for Physics-Informed Learning

Parallel Computing and Scientific Machine Learning

Uncertainty Programming Differentiable Programming Extended to Uncertainty Quantification

Parallel Computing and Scientific Machine Learning

Global Sensitivity Analysis

Parallel Computing and Scientific Machine Learning

From Optimization to Probabilistic Programming

Parallel Computing and Scientific Machine Learning

Code Profiling and Optimization (in Julia)

Parallel Computing and Scientific Machine Learning

GPU Programming in Julia

Parallel Computing and Scientific Machine Learning

Parallel Computing From SIMD to SIMT

Parallel Computing and Scientific Machine Learning

Partial Differential Equations (PDEs), Convolutions, and the Mathematics of Locality

Parallel Computing and Scientific Machine Learning

Differentiable Programming Part 2 Adjoint Derivation for (Neural) ODEs and Nonlinear Solve

Parallel Computing and Scientific Machine Learning

Differentiable Programming Part 1 Reverse-Mode AD Implementation

Parallel Computing and Scientific Machine Learning

Basic Parameter Estimation, Reverse-Mode AD, and Inverse Problems

Parallel Computing and Scientific Machine Learning

Solving Stiff Ordinary Differential Equations

Parallel Computing and Scientific Machine Learning

Forward-Mode Automatic Differentiation (AD) via High Dimensional Algebras

Parallel Computing and Scientific Machine Learning

Ordinary Differential Equations 2 Discretizations and Stability

Parallel Computing and Scientific Machine Learning

Ordinary Differential Equations 1 Applications and Solution Characteristics

Parallel Computing and Scientific Machine Learning

The Different Flavors of Parallelism Parallel Programming Models

Parallel Computing and Scientific Machine Learning

The Basics of Single Node Parallel Computing

Parallel Computing and Scientific Machine Learning

How Loops Work 2 Computationally-Efficient Discrete Dynamics

Parallel Computing and Scientific Machine Learning

How Loops Work 1 An Introduction to the Theory of Discrete Dynamical Systems

Parallel Computing and Scientific Machine Learning

Introduction to Scientific Machine Learning 1 Deep Learning as Function Approximation

Parallel Computing and Scientific Machine Learning

Introduction to Scientific Machine Learning 2 Physics-Informed Neural Networks

Parallel Computing and Scientific Machine Learning

Optimizing Serial Code in Julia 1 Memory Models, Mutation, and Vectorization

Parallel Computing and Scientific Machine Learning

Getting Started with Julia (for Experienced Programmers)

Parallel Computing and Scientific Machine Learning

Optimizing Serial Code in Julia 2 Type inference, function specialization, and dispatch

Parallel Computing and Scientific Machine Learning

Parallel Computing and Scientific Machine Learning Course Syllabus

Parallel Computing and Scientific Machine Learning