Comparing the performance of Hebbian against backpropagation learning using convolutional neural networks von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Hebbian semi-supervised learning in a sample efficiency setting von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Scalable bio-inspired training of Deep Neural Networks with FastHebb von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Fassold, Hannes, Amato, Giuseppe

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Evaluating Hebbian Learning in a Semi-supervised Setting von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Training Convolutional Neural Networks with Competitive Hebbian Learning Approaches von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Hebbian Learning Meets Deep Convolutional Neural Networks von Amato, Giuseppe, Carrara, Fabio, Falchi, Fabrizio, Gennaro, Claudio, Lagani, Gabriele

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FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level von Lagani, Gabriele, Gennaro, Claudio, Fassold, Hannes, Amato, Giuseppe

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Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical Imaging von Ciampi, Luca, Lagani, Gabriele, Amato, Giuseppe, Falchi, Fabrizio

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Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level von Lagani, Gabriele, Gennaro, Claudio, Fassold, Hannes, Amato, Giuseppe

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Hebbian Semi-Supervised Learning in a Sample Efficiency Setting von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Training Convolutional Neural Networks With Hebbian Principal Component Analysis von Lagani, Gabriele, Amato, Giuseppe, Falchi, Fabrizio, Gennaro, Claudio

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Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical Imaging von Ciampi, Luca, Lagani, Gabriele, Amato, Giuseppe, Falchi, Fabrizio

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Deep Features for CBIR with Scarce Data using Hebbian Learning von Lagani, Gabriele, Bacciu, Davide, Gallicchio, Claudio, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey von Lagani, Gabriele, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level von Lagani, Gabriele, Gennaro, Claudio, Fassold, Hannes, Amato, Giuseppe

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Assessing Pattern Recognition Performance of Neuronal Cultures through Accurate Simulation von Lagani, Gabriele, Mazziotti, Raffaele, Falchi, Fabrizio, Gennaro, Claudio, Cicchini, Guido Marco, Pizzorusso, Tommaso, Cremisi, Federico, Amato, Giuseppe

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Deep Features for CBIR with Scarce Data using Hebbian Learning von Lagani, Gabriele, Bacciu, Davide, Gallicchio, Claudio, Falchi, Fabrizio, Gennaro, Claudio, Amato, Giuseppe

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