Tools for exploiting Morphological Symmetries in robotics
On-the-fly generator of space-group irreducible representations
Isomorphisms of quiver representations applied to neural networks.
many powerful tools for studying irreducible representations of SU(n), including making animations of hadron flavor-state multiplets
AIDN is a deep learning algorithm to represent any finitely-presented algebraic object with a set of deep neural networks.
Computes representation matrices for Lie groups
Drafts of textbooks. One on the math inspired by supersymmetric field theories. One on low dimensional (below 3+1) integrable physics.
Search for non-trivial elements of the kernel of the Burau representation of the four-strand braid group.
A Python-based Rubik's Cube simulator and visualizer using matrix algebra for efficient representation, manipulation, and visualization of the cube's state. Includes a group theory approach to cube operations and a proof-of-concept visualization module using Matplotlib.
Very simple version of the code used for the experiments in the paper Hidden Activations Are Not Enough: A General Approach to Neural Networks Predictions.
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