575 citations · 880 across the 16 of their papers we have counts for
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The Impact of Stochasticity on the Rashomon Effect in Machine Learning
Andrea Apicella, Francesco Isgrò, Andrea Pollastro +1
Neural network training is inherently stochastic, with factors such as weight initialization leading to distinct models despite comparable predictive performance. This phenomenon i…
It's All in the Way You Say It: The Role of Information Representation in LLM-Based Glycemic-Event Prediction
Andrea Apicella, Pasquale Arpaia, Matteo Orefice +2
Large Language Models (LLMs) are increasingly being investigated for physiological time-series prediction, yet their effectiveness may depend not only on the model itself, but also…
Instance-Adaptive Parametrization for Amortized Variational Inference
Andrea Pollastro, Andrea Apicella, Francesco Isgrò +1
Variational autoencoders (VAEs) rely on amortized variational inference to enable efficient posterior approximation, but this efficiency comes at the cost of a shared parametrizati…
Don't stop me now: How Validation Criteria Affect Checkpoint Selection and Early Stopping
Andrea Apicella, Francesco Isgrò, Andrea Pollastro +1
Checkpoint selection is a standard component of neural network training, yet the validation criterion used to select a checkpoint is often chosen heuristically. Moreover, the same…