As part of adding support for a Torch operator in Torch-MLIR, it is usually necessary to define a shape and dtype function so that the compiler can infer the shapes and dtypes of result tensors for ...

This is a PyTorch implementation of graph-adaptive activation functions for Graph Neural Networks (GNNs). For any questions or suggestions, please e-mail Bianca Iancu at bianca.iancu026@gmail.com or ...

HOPE consists of four steps to predict microbial functions, including data input, microbial co-occurrence network construction, graph embedding generation, and function prediction. The input are 16s ...

Abstract: A graphical interpretation of the realization of symmetric Boolean functions with threshold logic elements is presented, from which a systematic synthesis method is developed. Theoretically, ...

In survival analysis with competing risks, the transformation model allows different functions between the outcome and explanatory variables. However, the model's prediction accuracy and the ...