Machine Learning Seminar

External homepage

machine learning mathematical physics commutative algebra algebraic geometry algebraic topology combinatorics differential geometry number theory representation theory

University of Nottingham

Audience:	Researchers in the topic
Seminar series times:	No fixed schedule
Organizers:	Alexander Kasprzyk, Lorenzo De Biase, Tom Oliver, Sara Veneziale
	*contact for this listing

Online machine learning in pure mathematics seminar, typically held on Wednesday. This seminar takes place online via Zoom.

For recordings of past talks and copies of the speaker's slides, please visit the seminar homepage at: kasprzyk.work/seminars/ml.html

Upcoming talks

Past talks

Your time			Speaker	Title
Wed	Sep 27	14:00	Rahul Sarkar	A framework for generating inequality conjectures
Wed	Oct 18	09:00	Felix Schremmer	Machine learning assisted exploration for affine Deligne-Lusztig varieties

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Your time			Speaker	Title
Wed	Sep 20	09:00	Bruno Gavranović	Fundamental Components of Deep Learning: A category-theoretic approach
Wed	Sep 06	14:00	Charlotte Aten	Discrete neural nets and polymorphic learning
Wed	Aug 02	09:00	Honglu Fan	Local uniformization, Hilbert scheme of points and reinforcement learning
Wed	Jul 26	09:00	Le Quoc Tung	Algorithmic and theoretical aspects of sparse deep neural networks
Wed	Jul 12	09:00	Challenger Mishra	Mathematical conjecture generation and Machine Intelligence
Wed	Jul 05	15:00	Thomas Gebhart	Specifying Local Constraints in Representation Learning with Cellular Sheaves
Wed	Jun 21	09:00	Edward Pearce-Crump	Exploring group equivariant neural networks using set partition diagrams
Wed	Jun 14	09:00	Vasco Brattka	On the Complexity of Computing Gödel Numbers
Wed	May 31	09:00	Alvaro Torras Casas	Dataset comparison using persistent homology morphisms
Wed	May 24	09:00	Taejin Paik	Isometry-Invariant and Subdivision-Invariant Representations of Embedded Simplicial Complexes
Wed	May 03	09:00	Daniel Platt	Group invariant machine learning by fundamental domain projections
Wed	Apr 26	09:00	Bastian Rieck	Curvature for Graph Learning
Wed	Apr 19	15:00	Christoph Hertrich	Understanding Neural Network Expressivity via Polyhedral Geometry
Wed	Apr 12	15:00	Vasco Portilheiro	Barriers to Learning Symmetries
Wed	Apr 05	09:00	Yang-Hui He	Universes as Bigdata: Physics, Geometry and Machine-Learning
Wed	Mar 29	14:00	Eduardo Paluzo-Hidalgo	An introduction to Simplicial-map Neural Networks
Wed	Mar 22	10:00	Patrizio Frosini	Some recent results on the theory of GENEOs and its application to Machine Learning
Wed	Mar 15	15:00	Julia Lindberg	Estimating Gaussian mixtures using sparse polynomial moment systems
Wed	Mar 08	10:00	Nick Vannieuwenhoven	Group-invariant tensor train networks for supervised learning
Wed	Feb 22	16:00	Guido Montufar	Geometry and convergence of natural policy gradient methods
Wed	Feb 15	10:00	Kathlén Kohn	The Geometry of Linear Convolutional Networks
Wed	Feb 08	10:00	Manolis Tsakiris	Unlabelled Principal Component Analysis
Mon	Sep 12	14:00	Anindita Maiti	Non-perturbative Non-Lagrangian Neural Network Field Theories
Fri	Jul 01	13:00	Alexei Vernitski	Using machine learning to solve mathematical problems and to search for examples and counterexamples in pure maths research
Wed	Sep 29	12:00	Tom Oliver	Supervised learning of arithmetic invariants

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