4 citations · 8 across the 7 of their papers we have counts for
3 papers · 1 filter
Neural Diffusion Processes for Physically Interpretable Survival Prediction
Alessio Cristofoletto, Cesare Rollo, Giovanni Birolo +1
We introduce DeepFHT, a survival-analysis framework that couples deep neural networks with first hitting time (FHT) distributions from stochastic process theory. Time to event is r…
The Advantage of Fine-Grained Training
Davide Pirovano, Federico Milanesio, Michele Caselle +2
In classification problems, models are trained to predict a class label based on the input data features. However, class labels are organized hierarchically in many datasets. While…
Beyond Cox Models: Assessing the Performance of Machine-Learning Methods in Non-Proportional Hazards and Non-Linear Survival Analysis
Ivan Rossi, Flavio Sartori, Cesare Rollo +3
Survival analysis often relies on Cox models, assuming both linearity and proportional hazards (PH). This study evaluates machine and deep learning methods that relax these constra…