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Author:
None
Summary:
Construct epsilon-machines to generate symbol sequences with ground truth causal structure and information-theoretic complexity for studying neural network learning dynamics.
Latest version:
0.2.1
Required dependencies:
automata-lib
|
graphviz
|
hnswlib
|
ipython
|
matplotlib
|
nanobind
|
networkx
|
numpy
|
orjson
|
pdoc
|
pyarrow
|
scikit-umfpack
|
scipy
|
sympy
Optional dependencies:
cupy-cuda13x
|
cuvs-cu13
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