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pro vyhledávání: '"Bounou, Oumayma"'
Autor:
Shen, Xi, Pastrolin, Ilaria, Bounou, Oumayma, Gidaris, Spyros, Smith, Marc, Poncet, Olivier, Aubry, Mathieu
Historical watermark recognition is a highly practical, yet unsolved challenge for archivists and historians. With a large number of well-defined classes, cluttered and noisy samples, different types of representations, both subtle differences betwee
Externí odkaz:
http://arxiv.org/abs/1908.10254
Over the past few years, differentiable optimization has gained in maturity and attractivity within both machine learning and robotics communities. It consists in computing the derivatives of a given optimization problem which can then be used by lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______165::a198d17f8087af92c20f517b12e971a1
https://hal.science/hal-03786820/file/oumayma_cdc_vff.pdf
https://hal.science/hal-03786820/file/oumayma_cdc_vff.pdf
Akademický článek
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Publikováno v:
NeurIPS 2021-Thirty-fifth Conference on Neural Information Processing Systems Year
NeurIPS 2021-Thirty-fifth Conference on Neural Information Processing Systems Year, Dec 2021, Sydney / Virtual, Australia
Advances in Neural Information Processing Systems
NeurIPS 2021-Thirty-fifth Conference on Neural Information Processing Systems Year, Dec 2021, Sydney / Virtual, Australia
Advances in Neural Information Processing Systems
International audience; Identifying an effective model of a dynamical system from sensory data and using it for future state prediction and control is challenging. Recent data-driven algorithms based on Koopman theory are a promising approach to this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::df798d003c4c1dd3ae12bf4933bd2847
https://hal.inria.fr/hal-03405911
https://hal.inria.fr/hal-03405911