Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686
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Updated
Jul 28, 2021 - Python
Meta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686
Code to accompany our paper "The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks"
Code for paper NeurIPS AMHN 2023
Computational Neuroscience projects.
Code for Computational Neuroscience course 2020/2021 @ UniPi
Differentiable Plasticity: A Meta-Learning Framework for Evolving Universal Learning Rules : This work synthesizes concepts from: Hebbian neuroscience (activity-dependent synaptic modification) Meta-learning (learning to learn) Differentiable programming (end-to-end gradient flow) Neuroplasticity (adaptive weight modification)
Project Neural Genesis — A brain-inspired AI architecture based on the Pr-Al dual-gradient axis theory
Towards a biologically plausible model of LGN-V1 pathways (Lian et al 2019)
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