For an up-to-date publication list, have a look at my Google scholar page.

Learning probability distributions of sensory inputs with Monte Carlo Predictive Coding

Gaspard Oliviers, Rafal Bogacz, Alexander Meulemans In submission

Structured entity extraction using large language models

Haolun Wu, Ye Yuan, Liana Mikaelyan, Alexander Meulemans, Xue Liu, James Hensman, Bhaskar Mitra In submission

Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis

Alexander Meulemans*, Simon Schug*, Seijin Kobayashi*, Nathaniel Daw, Gregory Wayne NeurIPS 2023 (Spotlight presentation)

The least-control principle for learning at equilibrium

Alexander Meulemans*, Nicolas Zucchet*, Seijin Kobayashi*, Johannes von Oswald, João Sacramento NeurIPS 2022 (Oral presentation and award nomination)

Minimizing Control for Credit Assignment with Strong Feedback

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

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