Boshko Koloski

HorNets: Learning from Discrete and Continuous Signals with Routing Neural Networks

2025 · arXiv (Cornell University)

Construction of neural network architectures suitable for learning from both continuous and discrete tabular data is a challenging research endeavor. Contemporary high-dimensional tabular data sets are often characterized by a relatively small instance count, requiring …