Search Results for author: Matilde Tristany Farinha

Found 3 papers, 3 papers with code

Minimizing Control for Credit Assignment with Strong Feedback

1 code implementation14 Apr 2022 Alexander Meulemans, Matilde Tristany Farinha, Maria R. Cervera, João Sacramento, Benjamin F. Grewe

Building upon deep feedback control (DFC), a recently proposed credit assignment method, we combine strong feedback influences on neural activity with gradient-based learning and show that this naturally leads to a novel view on neural network optimization.

Credit Assignment in Neural Networks through Deep Feedback Control

2 code implementations NeurIPS 2021 Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe

The success of deep learning sparked interest in whether the brain learns by using similar techniques for assigning credit to each synaptic weight for its contribution to the network output.

Equilibrium Propagation for Complete Directed Neural Networks

1 code implementation15 Jun 2020 Matilde Tristany Farinha, Sérgio Pequito, Pedro A. Santos, Mário A. T. Figueiredo

Artificial neural networks, one of the most successful approaches to supervised learning, were originally inspired by their biological counterparts.

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