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Found 5 papers, 2 papers with code
A New Spectral Method for Latent Variable Models
This paper presents an algorithm for the unsupervised learning of latent variable models from unlabeled sets of data.
Robust estimation of tree structured models
Consider the problem of learning undirected graphical models on trees from corrupted data.
Designing weights for quartet-based methods when data is heterogeneous across lineages
Second, we test and compare the performance of several quartet-based methods for phylogenetic tree reconstruction (namely, Quartet Puzzling, Weight Optimization and Wilson's method) in combination with ASAQ weights and other weights based on algebraic and semi-algebraic methods or on the paralinear distance.
A novel algebraic approach to time-reversible evolutionary models
In the last years, algebraic tools have been proven useful in phylogenetic reconstruction and model selection through the study of phylogenetic invariants.
Phylogenetic invariants: straightforward from the general Markov to equivariant models
With the aim of enlarging the practical uses of algebraic phylogenetics, in this paper we prove that phylogenetic invariants for trees evolving under equivariant models can be derived from phylogenetic invariants for the general Markov model, without the need of representation theory.
