Edge Selection for the Effective use of Piecewise-Constant Distributions as Neural Network Outputs for Event Prediction
The study investigates using categorical distributions as neural network outputs for predicting future events in temporal sequences. By modeling these predictions as piecewise-constant density functions, the method outperforms other output heads on existing datasets and introduces new benchmarks. It suggests that the best model choice depends heavily on the data structure.