Lecture and tutorial recordings
https://www.youtube.com/@mlmtp23/videos
Lecture slides
Meta-Heuristic for Physics (Steve Abel):
Calabi-Yau metrics from Neural Networks (Magdalena Larfors):
Intro to ML, RL and RL application to Knot Theory (Fabian Ruehle)
RL for Knot Theory (Andras Juhasz)
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:
Tutorial 2 on Tuesday: Quantum Annealing
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