Gabriele Lagani

According to our database, Gabriele Lagani authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Scalable bio-inspired training of Deep Neural Networks with FastHebb.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Hannes Fassold, Giuseppe Amato

Neurocomputing, 2024

2023

Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

CoRR, 2023

Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

CoRR, 2023

Scaling Bio-Inspired Neural Features to Real-World Image Retrieval Problems.

Gabriele Lagani

Proceedings of the 31st Symposium of Advanced Database Systems, 2023

AIMH Lab for a Susteinable Bio-Inspired AI.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Proceedings of the Italia Intelligenza Artificiale, 2023

2022

Comparing the performance of Hebbian against backpropagation learning using convolutional neural networks.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Neural Comput. Appl., 2022

FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level.

Gabriele Lagani, Claudio Gennaro, Hannes Fassold, Giuseppe Amato

Proceedings of the Similarity Search and Applications - 15th International Conference, 2022

Recent Advancements on Bio-Inspired Hebbian Learning for Deep Neural Networks.

Gabriele Lagani

Proceedings of the 30th Italian Symposium on Advanced Database Systems, 2022

Deep Features for CBIR with Scarce Data using Hebbian Learning.

Gabriele Lagani, Davide Bacciu, Claudio Gallicchio, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Proceedings of the CBMI 2022: International Conference on Content-based Multimedia Indexing, Graz, Austria, September 14, 2022

2021

Hebbian semi-supervised learning in a sample efficiency setting.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Neural Networks, 2021

Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation.

Gabriele Lagani, Raffaele Mazziotti, Fabrizio Falchi, Claudio Gennaro, Guido Marco Cicchini, Tommaso Pizzorusso, Federico Cremisi, Giuseppe Amato

Proceedings of the 10th International IEEE/EMBS Conference on Neural Engineering, 2021

Evaluating Hebbian Learning in a Semi-supervised Setting.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Training Convolutional Neural Networks with Competitive Hebbian Learning Approaches.

Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

2020

Training Convolutional Neural Networks With Hebbian Principal Component Analysis.

Gabriele Lagani, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro

CoRR, 2020

2019

Hebbian Learning Meets Deep Convolutional Neural Networks.

Giuseppe Amato, Fabio Carrara, Fabrizio Falchi, Claudio Gennaro, Gabriele Lagani

Proceedings of the Image Analysis and Processing - ICIAP 2019, 2019