The least-control principle for learning at equilibrium

Alexander Meulemans*, Nicolas Zucchet*, Seijin Kobayashi*, Johannes von Oswald, João Sacramento Submitted to NeurIPS 2022

Minimizing Control for Credit Assignment with Strong Feedback

Alexander Meulemans*, Matilde Tristany Farinha*, Maria R. Cervera*, João Sacramento, Benjamin F. Grewe ICML 2022 (Spotlight presentation)

Credit Assignment in Neural Networks through Deep Feedback Control

Alexander Meulemans*, Matilde Tristany Farinha*, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe NeurIPS 2021 (Spotlight presentation) (Talk)

Challenges for Using Impact Regularizers to Avoid Negative Side Effects

David Lindner*, Kyle Matoba*, Alexander Meulemans* SafeAI - AAAI 2021

Neural networks with late-phase weights

Johannes von Oswald*, Seijin Kobayashi*, Alexander Meulemans, Christian Henning, Benjamin F. Grewe, João Sacramento ICLR 2021

Continual Learning in Recurrent Neural Networks

Benjamin Ehret*, Christian Henning*, Maria R. Cervera*, Alexander Meulemans, Johannes von Oswald, Benjamin F. Grewe ICLR 2021

A Theoretical Framework for Target Propagation

Alexander Meulemans, Francesco S. Carzaniga, Johan A.K. Suykens, João Sacramento, Benjamin F. Grewe NeurIPS 2020 (Spotlight presentation) (Talk)

*Equal contribution