Alexander Meulemans

According to our database, Alexander Meulemans authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Learning probability distributions of sensory inputs with Monte Carlo predictive coding.

Gaspard Oliviers, Rafal Bogacz, Alexander Meulemans

PLoS Comput. Biol., 2024

Multi-agent cooperation through learning-aware policy gradients.

Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake A. Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento

CoRR, 2024

Structured Entity Extraction Using Large Language Models.

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

CoRR, 2024

Learning to Extract Structured Entities Using Language Models.

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

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

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

Alexander Meulemans, Simon Schug, Seijin Kobayashi, Nathaniel Daw, Gregory Wayne

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

The least-control principle for learning at equilibrium.

Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento

CoRR, 2022

The least-control principle for local learning at equilibrium.

Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Minimizing Control for Credit Assignment with Strong Feedback.

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

Proceedings of the International Conference on Machine Learning, 2022

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural networks with late-phase weights.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

Continual learning in recurrent neural networks.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

Challenges for Using Impact Regularizers to Avoid Negative Side Effects.

David Lindner, Kyle Matoba, Alexander Meulemans

Proceedings of the Workshop on Artificial Intelligence Safety 2021 (SafeAI 2021) co-located with the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), 2021

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

A Theoretical Framework for Target Propagation.

Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens, João Sacramento, Benjamin F. Grewe

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020