Gabriele Lagani

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 19

Top Topics

Labeled Samples

Hebbian Learning

Top Venues

Publications

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Hannes Fassold, Giuseppe Amato
Scalable bio-inspired training of Deep Neural Networks with FastHebb. Neurocomputing 595 (2024)
Gabriele Lagani
Scaling Bio-Inspired Neural Features to Real-World Image Retrieval Problems. SEBD (2023)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey. CoRR (2023)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey. CoRR (2023)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
AIMH Lab for a Susteinable Bio-Inspired AI. Ital-IA (2023)
Gabriele Lagani, Davide Bacciu, Claudio Gallicchio, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Deep Features for CBIR with Scarce Data using Hebbian Learning. CBMI (2022)
Gabriele Lagani, Claudio Gennaro, Hannes Fassold, Giuseppe Amato
FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level. CoRR (2022)
Gabriele Lagani
Recent Advancements on Bio-Inspired Hebbian Learning for Deep Neural Networks. SEBD (2022)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Comparing the performance of Hebbian against backpropagation learning using convolutional neural networks. Neural Comput. Appl. 34 (8) (2022)
Gabriele Lagani, Davide Bacciu, Claudio Gallicchio, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Deep Features for CBIR with Scarce Data using Hebbian Learning. CoRR (2022)
Gabriele Lagani, Claudio Gennaro, Hannes Fassold, Giuseppe Amato
FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level. SISAP (2022)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Training Convolutional Neural Networks with Competitive Hebbian Learning Approaches. LOD (2021)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Hebbian Semi-Supervised Learning in a Sample Efficiency Setting. CoRR (2021)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Hebbian semi-supervised learning in a sample efficiency setting. Neural Networks 143 (2021)
Gabriele Lagani, Raffaele Mazziotti, Fabrizio Falchi, Claudio Gennaro, Guido Marco Cicchini, Tommaso Pizzorusso, Federico Cremisi, Giuseppe Amato
Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation. NER (2021)
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
Evaluating Hebbian Learning in a Semi-supervised Setting. LOD (2021)
Gabriele Lagani, Raffaele Mazziotti, Fabrizio Falchi, Claudio Gennaro, Guido Marco Cicchini, Tommaso Pizzorusso, Federico Cremisi, Giuseppe Amato
Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation. CoRR (2020)
Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro
Training Convolutional Neural Networks With Hebbian Principal Component Analysis. CoRR (2020)
Giuseppe Amato, Fabio Carrara, Fabrizio Falchi, Claudio Gennaro, Gabriele Lagani
Hebbian Learning Meets Deep Convolutional Neural Networks. ICIAP (1) (2019)