Mehdi Cherti
Mehdi Cherti
Helmholtz AI
Verified email at - Homepage
Cited by
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Digits that are not: Generating new types through deep neural nets
A Kazakçı, C Mehdi, B Kégl
arXiv preprint arXiv:1606.04345, 2016
Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach
LMM Le, B Kégl, A Gramfort, C Marini, D Nguyen, M Cherti, S Tfaili, ...
Talanta 184, 260-265, 2018
The RAMP framework: from reproducibility to transparency in the design and optimization of scientific workflows
B Kégl, A Boucaud, M Cherti, A Kazakci, A Gramfort, G Lemaitre, ...
Out-of-class novelty generation: an experimental foundation
M Cherti, B Kégl, A Kazakçı
2017 IEEE 29th International Conference on Tools with Artificial …, 2017
De novo drug design with deep generative models: an empirical study
M Cherti, B Kégl, A Kazakçı
ICLR workshop, 2017
Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy
L Le, C Marini, A Gramfort, D Nguyen, M Cherti, S Tfaili, A Tfayli, ...
arXiv preprint arXiv:1705.07099, 2017
Spurious samples in deep generative models: bug or feature?
B Kégl, M Cherti, A Kazakçı
arXiv preprint arXiv:1810.01876, 2018
Deep generative neural networks for novelty generation : a foundational framework, metrics and experiments
M Cherti
Université Paris-Saclay, 2018
InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification
L Boussioux, T Giro-Larraz, C Guille-Escuret, M Cherti, B Kégl
arXiv preprint arXiv:1906.11898, 2019
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