Maxime Wabartha

Zaimi, A.*, Wabartha, M.*, Herman, V., Antonsanti, P. L., Perone, C. S., & Cohen-Adad, J. (2018). “AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks”. Nature Scientific reports, 8(1), 1-11.
[paper][code]

Wabartha, M., Durand, A., Francois-Lavet, V., & Pineau, J. (2018). “Sampling diverse neural networks for exploration in reinforcement learning”. NeurIPS Workshop on Bayesian Deep Learning.
[paper]

Wabartha, M., Durand, A., Francois-Lavet, V., & Pineau, J. (2019). “Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks”. NeurIPS Workshop on Safety and Robustness in Decision Making.
[code]

Wabartha, M., Durand, A., Francois-Lavet, V., & Pineau, J. (2020). “Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks”. International Joint Conference on Artificial Intelligence, 2140-2147.
[paper][code]

Mangeat, G., Ouellette, R., Wabartha, M., De Leener, B., Platt ́en, M., Danylait ́e Karrenbauer, V., … & Granberg, T. (2020). “Machine Learning and Multiparametric Brain MRI to Differentiate Hereditary Diffuse Leukodystrophy with Spheroids from Multiple Sclerosis”. Journal of Neuroimaging.
[paper]

Wabartha, M. & Pineau, J. (2023). “Piecewise Linear Parametrization of Policies for Interpretable Deep Reinforcement Learning”. NeurIPS Workshop on XAI in Action. [paper]