There is a nice example in @stephaneguindon.bsky.social's Ph.D thesis p.55

theses.hal.science/tel-00843343...

The design matrix of the regression should be nPairs x nBranches, and have a 1 at coordinates (i,j) such that branch j belongs to the path defined by pair i in the tree, 0 otherwise.

I think one way to do this is the least squares method, which gives you the set of branch lengths on your given topology such that the sum of squared differences between your given distances and the distances on the tree are minimal.

Come hear about the latest advances in the field and discuss your own work at Centre Paul Langevin in beautiful Aussois.

Burak Yelmen from the University of Tartu will give a keynote presentation on "A perspective on generative neural networks in genomics with applications in synthetic data generation".

Claudia Solís-Lemus from the University of Wisconsin-Madison will give a keynote presentation on "The good, the bad and the ugly of deep learning in phylogenetic inference".

Anne-Florence Bitbol from EPFL will give a keynote presentation on "Coevolution-aware language models".