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Found 3 papers, 2 papers with code
Causal disentanglement of multimodal data
Causal representation learning algorithms discover lower-dimensional representations of data that admit a decipherable interpretation of cause and effect; as achieving such interpretable representations is challenging, many causal learning algorithms utilize elements indicating prior information, such as (linear) structural causal models, interventional data, or weak supervision.
Newton-Okounkov bodies of chemical reaction systems
Here, we introduce a new upper bound on this number, namely the `Newton-Okounkov body bound' of a chemical reaction network.
Numerical homotopies from Khovanskii bases
We present numerical homotopy continuation algorithms for solving systems of equations on a variety in the presence of a finite Khovanskii basis.
Algebraic Geometry 13P15, 14M25, 68W30
