Salta al contenuto principale
Ricerc@Sapienza
Toggle navigation
Home
Login
Home
Persone
adriano.barra@uniroma1.it
Adriano Barra
Professore Associato
Struttura:
DIPARTIMENTO DI SCIENZE DI BASE ED APPLICATE PER L'INGEGNERIA
E-mail:
adriano.barra@uniroma1.it
Pagina istituzionale corsi di laurea
Curriculum Sapienza
Pubblicazioni
Titolo
Pubblicato in
Anno
Hebbian dreaming for small datasets
NEURAL NETWORKS
2024
Statistical mechanics of learning via reverberation in bidirectional associative memories
PHYSICA. A
2024
About the de Almeida–Thouless line in neural networks
PHYSICA. A
2024
Inverse modeling of time-delayed interactions via the dynamic-entropy formalism
PHYSICAL REVIEW. E
2024
Supervised Hebbian learning
EUROPHYSICS LETTERS
2023
From Pavlov Conditioning to Hebb Learning
NEURAL COMPUTATION
2023
Dense Hebbian neural networks: A replica symmetric picture of supervised learning
PHYSICA. A
2023
Dense Hebbian neural networks: A replica symmetric picture of unsupervised learning
PHYSICA. A
2023
Ultrametric identities in glassy models of natural evolution
JOURNAL OF PHYSICS. A, MATHEMATICAL AND THEORETICAL
2023
Parallel learning by multitasking neural networks
JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT
2023
Quantifying heterogeneity to drug response in cancer–stroma kinetics
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2023
Thermodynamics of bidirectional associative memories
JOURNAL OF PHYSICS. A, MATHEMATICAL AND THEORETICAL
2023
Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers
ACS NANO
2023
The emergence of a concept in shallow neural networks
NEURAL NETWORKS
2022
Outperforming RBM Feature-Extraction Capabilities by "Dreaming" Mechanism
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2022
A fully automatic computational approach for precisely measuring organelle acidification
ACS APPLIED MATERIALS & INTERFACES
2022
Replica Symmetry Breaking in Dense Hebbian Neural Networks
JOURNAL OF STATISTICAL PHYSICS
2022
On the effective initialisation for restricted Boltzmann machines via duality with Hopfield model
NEURAL NETWORKS
2021
Annealing and Replica-Symmetry in Deep Boltzmann Machines
JOURNAL OF STATISTICAL PHYSICS
2020
Towards the development of human Immune System-on-a-chip platform
DRUG DISCOVERY TODAY
2019
1
2
seguente ›
ultima »
© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma