Code for the paper 'Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology'
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Updated
Feb 25, 2019 - Python
Code for the paper 'Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology'
Python bindings and API for the flagser C++ library (https://github.com/luetge/flagser).
A toolkit for discrete calculus.
A miscellaneous repository for anything having to do with computation in the context of Graph Theory
Drafts of textbooks. One on the math inspired by supersymmetric field theories. One on low dimensional (below 3+1) integrable physics.
Estimation of Neural Network Dimension using Algebraic Topology and Lie Theory.
Studying biomolecules with persistence homology
This package provides tools to work with Sullivan forms, Dupont forms, and the Dupont contraction from Sullivan to Dupont forms. In particular, it allows for the computation of the transferred homotopy commutative structure on Dupont forms.
Algorithm I made accompanying my Master's thesis.
A set of scripts for parsing definitions of graded (co)algebras.
Program (still in progress) for calculating resolutions of modules over the truncated Steenrod algebra 𝓐(1) at p = 2.
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