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Found 5 papers, 1 papers with code
Conditional Generative Modeling for De Novo Hierarchical Multi-Label Functional Protein Design
The availability of vast protein sequence information and rich functional annotations thereof has a large potential for protein design applications in biomedicine and synthetic biology.
Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings
Moreover -- and in contrast with other methods -- the hierarchical nature of hyperbolic space allows us to learn highly efficient representations and to improve the taxonomic consistency of the inferred hierarchies.
Finding significant combinations of features in the presence of categorical covariates
In high-dimensional settings, where the number of features p is typically much larger than the number of samples n, methods which can systematically examine arbitrary combinations of features, a huge 2^p-dimensional space, have recently begun to be explored.
Searching for significant patterns in stratified data
Significant pattern mining, the problem of finding itemsets that are significantly enriched in one class of objects, is statistically challenging, as the large space of candidate patterns leads to an enormous multiple testing problem.
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing
Westfall-Young light opens the door to significant pattern mining on large datasets that previously led to prohibitive runtime or memory costs.
