I am a currently a postdoc researcher at the Friedrich Miescher Institute in Basel 🇨🇭 in computational neuroscience and AI in the team of Friedemann Zenke. Prior to that, I completed my PhD in physics with Damien Querlioz at the Center for Nanoscience in Saclay 🇫🇷. I am interested in how artificial and biological neural networks learn efficiently and how circuit structure relates to computation. I am grateful to be funded by the Swiss National Science Fundation. You can find my CV here.

News

• (01/2024) - My paper on generalizing hEP to arbitrary network topologies with Jacobian homeostasis is accepted at ICLR 2024! 🎉
• (10/2023) - New paper on how non-contrastive SSL implicitly regularizes variance accepted at NeurIPS 2023! 🎉
• (07/2023) - The fractal plot I submitted to FMI’s science image competition, derived from holomorphic EP, have been selected and printed for display at the FMI!
• (03/2023) - I received the Thesis Prize from the Graduate School of Engineering Sciences and Systems from Paris-Saclay University! 🥇
• (02/2023) - I will attend and give a talk at the workshop on Recent advances in understanding artificial and biological neural networks in les Houches! 🏔
• (10/2022) - Holomorphic equilibrium propagation was selected as an “Oral” at NeurIPS 2022! 🎉
• (09/2022) - My paper on holomorphic equilibrium propagation (hEP) got accepted at NeurIPS 2022!
• (07/2022) - I was awarded a fellowship from the Swiss National Science Foundation! The goal of the project is to link cortical circuit motifs to there putative functions in the framework of predictive processing.

Featured publications

• Halvagal, M. S., Laborieux, A., & Zenke, F. (2023). Implicit variance regularization in non-contrastive SSL. In Thirty-seventh Conference on Neural Information Processing Systems. (proceedings)
• Laborieux, A., & Zenke, F. (2022). Holomorphic equilibrium propagation computes exact gradients through finite size oscillations. Advances in Neural Information Processing Systems, 35, 12950-12963. (proceedings)
• Laborieux, A., Ernoult, M., Hirtzlin, T., & Querlioz, D. (2021). Synaptic metaplasticity in binarized neural networks. Nature communications, 12(1), 1-12. (paper)
• Laborieux, A., Ernoult, M., Scellier, B., Bengio, Y., Grollier, J., & Querlioz, D. (2021). Scaling equilibrium propagation to deep convnets by drastically reducing its gradient estimator bias. Frontiers in neuroscience, 15, 129. (paper)