Research Programme
Topological Data Analysis
A ten-paper research programme applying persistent homology, Mapper, and related methods to poverty trajectory data from Understanding Society and the BHPS.
Papers
- Stage 0 — Foundations Paper 1 The Markov Memory Ladder Stage 0 In Progress
- Stage 1 — Core Methods Paper 2 Mapper for Interior Trajectory Structure Stage 1 Planned
- Stage 1 — Core Methods Paper 3 Zigzag Persistence for Business Cycle Topology Stage 1 Planned
- Stage 2 — Extensions Paper 4 Multi-Parameter Persistent Homology for Poverty Trap Detection Stage 2 Planned
- Stage 2 — Extensions Paper 5 Cross-National Welfare State Topology Stage 2 Planned
- Stage 2 — Extensions Paper 6 Intergenerational Topological Inheritance Stage 2 Planned
- Stage 3 — Applications Paper 7 Geometric Trajectory Forecasting Stage 3 Planned
- Stage 3 — Applications Paper 8 Graph Neural Networks on Household Social Graphs Stage 3 Planned
- Stage 3 — Applications Paper 9 Combinatorial Complex Neural Networks for Trajectory Analysis Stage 3 Planned
- Stage 3 — Applications Paper 10 Topological Fairness Analysis of Poverty Measurement Stage 3 Planned