Remi Monasson — accepted AI-conference papers

2024

Accelerated Sampling with Stacked Restricted Boltzmann Machines

Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco, Remi Monasson

ICLR 2024poster

Sampling complex distributions is an important but difficult objective in various fields, including physics, chemistry, and statistics. An improvement of standard Monte Carlo (MC) methods, intensively used in particular in the context of disordered systems, is Parallel Tempering, also called replica…

Cited by 7 Source ↗PDF ↗Scholar ↗

2024

Restoring balance: principled under/oversampling of data for optimal classification

Emanuele Loffredo, Mauro Pastore, Simona Cocco, Remi Monasson

ICML 2024poster

Class imbalance in real-world data poses a common bottleneck for machine learning tasks, since achieving good generalization on under-represented examples is often challenging. Mitigation strategies, such as under or oversampling the data depending on their abundances, are routinely proposed and tes…

Cited by 3 Source ↗PDF ↗code ↗Scholar ↗