Computational Physics and Machine Learning, Computational Science PhD program Fall and Spring 2021/2022

Morten Hjorth-Jensen [1, 2]
Anders Kvellestad [3]
[1] Department of Physics and Astronomy and Facility for Rare Isotope Beams, Michigan State University, USA
[2] Department of Physics and Center for Computing in Science Education (office FØ470), University of Oslo, Norway
[3] Department of Physics (office FØ447), University of Oslo, Norway

October 24-28 Linear regression and introduction

October 31 - November 4 Regularization and Lasso and Ridge regression

November 14-18 Resampling Methods

December 12 Logistic Regression

December 13-14 Optimization and Stochastic gradient methods

December 16 Support vector machines

December 17 Support vector machines

January 17 Neural Networks and the back propagation algorithm

January 24 Buildng a neural network code

January 31 Introduction to TensorFlow and Solving differential equations

February 7 Differential equations with neural networks

February 14 Discussion of project 2 and start convolutional neural networks

February 21 Convolutional neural networks

February 28 Convolutional and Recurrent Neural Networks

March 7 Recurrent neural networks and summary of deep learning methods

Projects Fall and Spring 2022/2023 (dates are tentative)

Project 1, Deadline January 31 (available December 12)

Project 2, Deadline May 31

Project 3, Deadline May 31