Machine Learning and Fundamental Physics

Physics 835: Collider Physics

Spring 2021

Instructor: Prof. Gary Shiu

Physics Department Course Reference Page

Course Info and Syllabus

Lecture Slides

Lecture 1: Overview

Lecture 2: Basics of Machine Learning

Lecture 3: Optimizers

Lecture 4: Linear Regression

Lecture 5: Logistic Regression

Lecture 6: Information Content

Lecture 7: Perceptron

Lecture 8: Support Vector Machine

Lecture 9: Kernel Methods

Lecture 10: Feedforward Neural Networks

Lecture 11: Convolutional Neural Networks

Lecture 12: Recurrent Neural Networks

Lecture 13: Unsupervised Learning I

Lecture 14: Unsupervised Learning II

Lecture 15: Variational methods & Mean Field Theory

Lecture 16: Generative Adversarial Networks

Lecture 17: Variational Autoencoder

Lecture 18: Topological Data Analysis

Exercises

Acknowledgments

See a similar course taught by Sven Krippendorf at LMU-Munich. We acknowledge him for sharing his insights.