5 papers
Dreaming improves memorization in a Hopfield model with bounded synaptic strength
Enzo Marinari, Saverio Rossi, Francesco Zamponi
The Hopfield model provides a paradigmatic framework for associative memory. Its classical implementation, based on the Hebbian learning rule, suffers from catastrophic forgetting:…
Modeling Protein Evolution via Generative Inference From Monte Carlo Chains to Population Genetics
Leonardo Di Bari, Thierry Mora, Andrea Pagnani +3
Generative models derived from large protein sequence alignments define complex fitness landscapes, but their utility for accurately modeling non-equilibrium evolutionary dynamics…
Pseudo-likelihood produces associative memories able to generalize, even for asymmetric couplings
Francesco D'Amico, Dario Bocchi, Luca Maria Del Bono +2
Energy-based probabilistic models learned by maximizing the likelihood of the data are limited by the intractability of the partition function. A widely used workaround is to maxim…
Functional bottlenecks can emerge from non-epistatic underlying traits
Anna Ottavia Schulte, Samar Alqatari, Saverio Rossi +1
Protein fitness landscapes frequently exhibit epistasis, where the effect of a mutation depends on the genetic context in which it occurs, i.e., the rest of the protein sequence. E…
Fluctuations and the limit of predictability in protein evolution
Saverio Rossi, Leonardo Di Bari, Martin Weigt +1
Protein evolution involves mutations occurring across a wide range of time scales. In analogy with disordered systems in statistical physics, this dynamical heterogeneity suggests…