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Maxime Lucas (12/3/2024): Revealing patterns in brain activity with persistent homology
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Classroom Contents
Applied Algebraic Topology Networks Seminar - Applications and Theory of Network Structure Through Topology and Algebra
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- 1 Cristian Bodnar (11/7/23): A Sheaf-based Approach to Graph Neural Networks
- 2 Dani Bassett (12/5/2023): Science as branched flow: A case study in citation disparities
- 3 Audun Myers (3/5/2024): Data Analysis Using Zigzag Persistence
- 4 Katie Morrison (4/2/2024) Predicting neural network dynamics from connectivity
- 5 Markus Reineke (6/4/2024): Quiver representations and neural networks
- 6 Marco Nurisso (10/1/2024): Interactions and topological synchronization in simplicial Kuramoto model
- 7 Maxime Lucas (12/3/2024): Revealing patterns in brain activity with persistent homology
- 8 Chunyin Siu (02/04/25): Homology and Homotopy Properties of Scale-Free Networks.
- 9 Karel Devriendt (03/04/25): Spanning trees, effective resistances and curvature on graphs
- 10 Lina Fajardo Gómez (04/01/25): Prodsimplicial Complexes and Applications to Word Reduction Pathways
- 11 Chris Kapulkin (05/06/25): An invitation to discrete homotopy theory
- 12 Carles Casacuberta (06/03/25): A chordless cycle filtration for network dimensionality detection.
- 13 Massimo Ferri (07/01/25): Steady and ranging: persistence without homology
- 14 Hubert Wagner (10/7/25): Beyond the shape of data: detecting spatial interactions
- 15 Evan Patterson (11/04/25): Networks as free categorical structures
