31 citations · 62 across the 14 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025★ 1 cited
A theoretical framework for overfitting in energy-based modeling
Giovanni Catania, Aurélien Decelle, Cyril Furtlehner +1
We investigate the impact of limited data on training pairwise energy-based models for inverse problems aimed at identifying interaction networks. Utilizing the Gaussian model as t…
cs.LG2023★ 1 cited
Explaining the effects of non-convergent sampling in the training of Energy-Based Models
Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle +1
In this paper, we quantify the impact of using non-convergent Markov chains to train Energy-Based models (EBMs). In particular, we show analytically that EBMs trained with non-pers…