-
Allow for running each iteration in a bootstrap multiple times with different fixed pairs (#9)
- Implemented with a new
n_repeats
kwarg forDiffPaSSModel.fit_bootstrap
- By performing several repeats of each bootstrap iteration, we can greedily select the best repeat by hard loss, and use that repeat to select the next set of fixed pairs. This should improve performance in hard cases.
- Implemented with a new
-
New tutorial notebook on graph alignment, covering
diffpass.train.GraphAlignment
and usingn_repeats
infit_bootstrap
(#11)
- Store hard and soft losses as Python scalars instead of 0-dimensional NumPy arrays (#3)
-
Unify type annotations for
group_sizes
(#7) -
Add possibility to include diagonals in
IntraGroupSimilarityLoss
computations (#5) -
Store hard and soft losses as Python scalars instead of 0-dimensional NumPy arrays (#3)
- Fix
fit_bootstrap
appending empty lists (#1)
- Change signature of
get_robust_pairs
(ebb160c)
- Add
remove_groups_not_in_both
function (876d017)
- First DiffPaSS public release