University of Oxford
ML in Maths and Physics 2023
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Lectures and tutorials

Lecture and tutorial recordings

https://www.youtube.com/@mlmtp23/videos

 

Lecture slides

Meta-Heuristic for Physics (Steve Abel): 

oxford_ml_2023_.pdf - 30.5 MB (pdf)

 

Calabi-Yau metrics from Neural Networks (Magdalena Larfors):

lecture1-mlcymetrics.pdf - 17.85 MB (pdf)
lecture2-mlcymetrics.pdf - 8.09 MB (pdf)

 

Intro to ML, RL and RL application to Knot Theory (Fabian Ruehle)

lecture_1_-_intro_to_ml.pdf - 15.84 MB (pdf)
lecture_2_-_intro_to_rl.pdf - 8.22 MB (pdf)
lecture_3_-_rl_appications_to_knot_theory.pdf - 19.76 MB (pdf)

 

RL for Knot Theory (Andras Juhasz)

unknotting.pdf - 1.27 MB (pdf)

 

Tutorials

Tutorial 1 on Monday: Introduction to ML

https://colab.research.google.com/github/callum-ryan-brodie/oxford-ml-physmath-school/blob/main/oxford_ml_physmath_school_notebook_1.ipynb

Tutorial 2 on Monday: Genetic algorithms

Notebooks: https://www.tinyurl.com/ga-ox-taxi  https://tinyurl.com/ga-ox-knapsol   https://tinyurl.com/ga-ox-min

Problem sheet:

GAs.pdf - 74.29 KB (pdf)

 

Tutorial 2 on Tuesday: Quantum Annealing

problem_sheet_1.pdf - 104.11 KB (pdf)

Notebooks (including solutions): https://www.dropbox.com/scl/fo/iydy4ngbsvfe5pmrxhdeb/h?dl=0&rlkey=ecsenwkl9mnnsdupr95mwms7n

 

Tutorial 1 on Thursday: Reinforcement Learning

https://colab.research.google.com/github/callum-ryan-brodie/oxford-ml-physmath-school/blob/main/oxford_ml_physmath_school_notebook_2.ipynb

Tutorial 2 on Thursday: 

https://github.com/edhirst/OxfordCYTutorial/tree/main 

 

Tutorial 1 on Friday: 

https://tinyurl.com/ml-ox-fano

Tutorial 2 on Friday: 

https://colab.research.google.com/drive/1Z-jzToRkrTHayB83J0UKogbbBGO5Zdho?usp=sharing