A Theoretical Framework for Target Propagation. - Alexander Meulemans; Francesco S. Carzaniga; Johan A. K. Suykens; João Sacramento; Benjamin F. Grewe (NeurIPS, 2020)

Continual Learning in Recurrent Neural Networks with Hypernetworks. - Benjamin Ehret; Christian Henning; Maria R. Cervera; Alexander Meulemans; Johannes von Oswald; Benjamin F. Grewe (CoRR, 2020)

Challenges for Using Impact Regularizers to Avoid Negative Side Effects. - David Lindner; Kyle Matoba; Alexander Meulemans (SafeAI@AAAI, 2021)

Continual learning in recurrent neural networks. - Benjamin Ehret; Christian Henning; Maria R. Cervera; Alexander Meulemans; Johannes von Oswald; Benjamin F. Grewe (ICLR, 2021)

Neural networks with late-phase weights. - Johannes von Oswald; Seijin Kobayashi; João Sacramento; Alexander Meulemans; Christian Henning; Benjamin F. Grewe (ICLR, 2021)

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)

Minimizing Control for Credit Assignment with Strong Feedback. - Alexander Meulemans; Matilde Tristany Farinha; Maria R. Cervera; João Sacramento; Benjamin F. Grewe (ICML, 2022)

The least-control principle for local learning at equilibrium. - Alexander Meulemans; Nicolas Zucchet; Seijin Kobayashi; Johannes von Oswald; João Sacramento (NeurIPS, 2022)

The least-control principle for learning at equilibrium. - Alexander Meulemans; Nicolas Zucchet; Seijin Kobayashi; Johannes von Oswald; João Sacramento (CoRR, 2022)

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)

Learning to Extract Structured Entities Using Language Models. - Haolun Wu; Ye Yuan 017; Liana Mikaelyan; Alexander Meulemans; Xue Liu 004; James Hensman; Bhaskar Mitra 001 (EMNLP, 2024)

Structured Entity Extraction Using Large Language Models. - Haolun Wu; Ye Yuan 017; Liana Mikaelyan; Alexander Meulemans; Xue Liu 001; James Hensman; Bhaskar Mitra 001 (CoRR, 2024)

Learning probability distributions of sensory inputs with Monte Carlo predictive coding. - Gaspard Oliviers; Rafal Bogacz; Alexander Meulemans (PLoS Comput. Biol., 2024)

Control-based theories for credit assignment in neural networks and reinforcement learning. - Alexander Meulemans (2024)

Multi-agent cooperation through learning-aware policy gradients. - Alexander Meulemans; Seijin Kobayashi; Johannes von Oswald; Nino Scherrer; Eric Elmoznino; Blake Aaron Richards; Guillaume Lajoie; Blaise Agüera y Arcas; João Sacramento (ICLR, 2025)

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training. - Johannes von Oswald; Nino Scherrer; Seijin Kobayashi; Luca Versari; Songlin Yang; Maximilian Schlegel; Kaitlin Maile; Yanick Schimpf; Oliver Sieberling; Alexander Meulemans; Rif A. Saurous; Guillaume Lajoie; et al. (CoRR, 2025)