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Found 2 papers, 2 papers with code
Meta-Learning Biologically Plausible Plasticity Rules with Random Feedback Pathways
In this study, we develop a meta-learning approach to discover interpretable, biologically plausible plasticity rules that improve online learning performance with fixed random feedback connections.
Physics-Constrained Predictive Molecular Latent Space Discovery with Graph Scattering Variational Autoencoder
In this work, we assess the predictive capabilities of a molecular generative model developed based on variational inference and graph theory in the small data regime.
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