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Found 3 papers, 2 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.
Wasserstein Weisfeiler-Lehman Graph Kernels
Most graph kernels are an instance of the class of $\mathcal{R}$-Convolution kernels, which measure the similarity of objects by comparing their substructures.
Ranked #7 on
Graph Classification
on NCI1
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
While many approaches to make neural networks more fathomable have been proposed, they are restricted to interrogating the network with input data.
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