Gabriele Lagani

Orcid: 0000-0003-4739-5778

According to our database1, Gabriele Lagani authored at least 15 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Scalable bio-inspired training of Deep Neural Networks with FastHebb.
Neurocomputing, 2024

2023
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey.
CoRR, 2023

Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey.
CoRR, 2023

Scaling Bio-Inspired Neural Features to Real-World Image Retrieval Problems.
Proceedings of the 31st Symposium of Advanced Database Systems, 2023

AIMH Lab for a Susteinable Bio-Inspired AI.
Proceedings of the Italia Intelligenza Artificiale, 2023

2022
Comparing the performance of Hebbian against backpropagation learning using convolutional neural networks.
Neural Comput. Appl., 2022

FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level.
Proceedings of the Similarity Search and Applications - 15th International Conference, 2022

Recent Advancements on Bio-Inspired Hebbian Learning for Deep Neural Networks.
Proceedings of the 30th Italian Symposium on Advanced Database Systems, 2022

Deep Features for CBIR with Scarce Data using Hebbian Learning.
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.
Neural Networks, 2021

Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation.
Proceedings of the 10th International IEEE/EMBS Conference on Neural Engineering, 2021

Evaluating Hebbian Learning in a Semi-supervised Setting.
Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Training Convolutional Neural Networks with Competitive Hebbian Learning Approaches.
Proceedings of the Machine Learning, Optimization, and Data Science, 2021

2020
Training Convolutional Neural Networks With Hebbian Principal Component Analysis.
CoRR, 2020

2019
Hebbian Learning Meets Deep Convolutional Neural Networks.
Proceedings of the Image Analysis and Processing - ICIAP 2019, 2019


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