AI and Deep Learning
I'm interested in Computer Vision, Geometric Deep Learning, Optimization and its applications in medical DL.
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Cortical Flow: A Diffeomorphic Mesh Deformation Network for Cortical Surface Reconstruction
Leo Lebrat, Rodrigo Santa Cruz, Frederic de Gournay, Pierrick Bourgeat, Jurgen Fripp, Darren Fu, Clinton Fookes, Olivier Salvado.
Conference on Neural Information Processing Systems (NeurIPS), 2021
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MongeNet: Efficient Sampler for Geometric Deep Learning
Leo Lebrat, Rodrigo Santa Cruz, Clinton Fookes, Olivier Salvado.
Conference on Computer Vision and Pattern Recognition (CVPR), 2021
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Going Deeper with Brain Morphometry using Neural Networks
Rodrigo Santa Cruz, Leo Lebrat, Pierrick Bourgeat, Vincent Doré, Jason Dowling, Jurgen Fripp, Clinton Fookes, Olivier Salvado.
IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021
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SMOCAM: SMOoth Conditional Attention Mask for 3D-Regression Models
Salamata Konate, Leo Lebrat, Rodrigo Santa Cruz, Pierrick Bourgeat, Vincent Doré, Jurgen Fripp, Andrew Bradley, Clinton Fookes, Olivier Salvado.
IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021
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DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction
Rodrigo Santa Cruz, Leo Lebrat, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado.
IEEE Winter Conference on Applications of Computer Vision (WACV), 2021
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Math publications
Before joining CSIRO my research focused on Optimal Transport and Optimization.
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3/4-Discrete Optimal Transport
Leo Lebrat, Frederic de Gournay, Jonas Kahn.
SIAM Journal on Scientific Computing, 2020
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Optimal Transport Approximation of 2-Dimensional Measures
Leo Lebrat, Frederic de Gournay, Jonas Kahn, Pierre Weiss.
SIAM Journal on Imaging Sciences, 2019
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Differentiation and regularity of semi-discrete optimal transport with respect to the parameters of the discrete measure
Frederic de Gournay, Jonas Kahn, Leo Lebrat.
Numerische Mathematik, 2018
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