Reading Groups

Machine Learning 2024/2025

Organisers: Hefin Lambley and Marc Truter

Time: Tuesday 3:00 pm B3.03 Term 3 2024/2025

Resources:  [B] Learning theory from first principles by Francis Bach, [BBSS]  Inverse problems and data assimilation: a machine learning approach by Eviatar Bach, Ricardo Baptista, Daniel Sanz-Alonso, and Andrew Stuart

Github Repository: https://github.com/marctruter/machinelearning

Week 2: Introductory Talk, Hefin Lambley and Marc Truter

Part I: Supervised learning

Week 3: Supervised learning [B, §2], Hefin Lambley and Marc Truter

Week 4: Linear regression [B, §3], Paweł Nosal 

Week 5: Optimisation [B, §5], Tarek Acila

Week 6: Kernel methods [B, §7], Alvaro Gonzalez Hernandez

Week 7: Neural Networks [B, §9], Pietro Wald and Marc Truter

Week 8: Group Theory and Machine Learning, Poppy Azmi

Part II: Generative modelling

Week 9: Diffusion models [BBSS, §13.4], Grega Saksida

Week 10: Autoencoders [BBSS, §13.5,13.6], James Town

K-stability 2024/2025

Organisers: Marc Truter

Time: Thursday 12:00 pm B1.12 Term 2 2024/2025

Resources:  K-stability lecture notes by Harold Blum

Week 3: Introduction to K-stability, Marc Truter

Week 4: K-stability of polarised varieties, Marc Truter

Week 5: Odaka's theorems, Alvaro Gonzalez Hernandez

Geometric Invariant Theory (GIT) 2024/2025

Organisers: Marc Truter

Time: Thursday 12:00 pm D1.07 Term 1 2024/2025

Resources:  Moduli problems and Geometric Invariant theory lecture notes by Victoria Hoskins

Week 2: Introduction to Moduli problems and GIT, Marc Truter

Week 3: Moduli problems, Arnaud Vilpert 

Week 4: Groups and actions, Chunkai Xu

Week 5: Affine GIT, Alvaro Gonzalez Hernandez

Week 6: Projective GIT, Tommaso Faustini

Week 7: Stability, Marc Truter

Week 8: Moduli of vector bundles I, Peize Liu

Week 9: Moduli of vector bundles II, Chunkai Xu

Week 10: Moduli of hypersurfaces, Peize Liu

Week 11: Kirwan blowup and moduli space of cubics, Peize Liu