David SABBAGH
@DavSabbagh
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Machine Learning PhD student @INRIA. Working on AI & Neuroscience.
Paris, France
Joined May 2018
Présentation aux étudiants du master MVA des projets du laboratoire développés au sein du @Bernoulli_Lab, en équipe ! @DavSabbagh @J_Cartailler @FrançoisKimmig
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@Bernoulli_Lab présent au forum du master MVA, voir aussi nos offres de stages en ligne https://t.co/Vw5AglYOdL
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L’@aphp, c’est aussi la possibilité de mettre autour de la même table des médecins, des data scientists, des ingénieurs et leurs étudiants ! Le projet EDS Peri’Op prend corps @Inria @Univ_Paris @Emissed @DavSabbagh @JadePerdereau @J_Cartailler @Bernoulli_Lab
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Coming up soon: a mooc to learn machine learning in Python with @scikit_learn
https://t.co/mkf8g2x44x 8 weeks, 4.5Hrs/wk, from zero to hero in machine learning: from knowing only basic Python to understanding ML Brought to you by @InriaLearnLab @sklearn_inria & @Inria_Academy
fun-mooc.fr
Build predictive models with scikit-learn and gain a practical understanding of the strengths and limitations of machine learning!
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At @Parietal_INRIA, together with @gzanitti, @Antonia_Machlou and @demwassermann, we develop a probabilistic programming language called NeuroLang where cognitive science hypotheses can be formulated and tested against heterogeneous data. @OHBM poster: https://t.co/8q6eLgVMaU
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8/ A plain language summary and press release can be found here:
elifesciences.org
Scientists have developed a computer model that can accurately predict brain age and could be used to combine different types of brain function tests to predict patient outcomes such as cognitive...
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[#DataScience] Comment déterminer l'âge du cerveau d'une personne vs son âge biologique ? Cet âge cérébral est-il lié à l'apparition de troubles neurodégénératifs ? 4 chercheurs @Parietal_INRIA publient leurs résultats dans @eLife !⤵️ https://t.co/MwnOycdAWC
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I am very excited to share our latest work published in @eLife! We combined #MEG, #fMRI and #MRI for #BrainAge prediction & #biomarker development. Each modality added unique information & enhanced brain-behavior mapping! https://t.co/iCLYKsuUWY Thread👇
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Excited to share our paper @NeuroImage_EiC by @DavSabbagh with @PierreAblin @GaelVaroquaux @agramfort
https://t.co/ke0wO8aqwk Nonlinear subject-level regression on M/EEG using linear models without source localization: theory + empirical benchmarks Thread👇
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4 papers accepted for NeurIPS 2019 https://t.co/rQh1cly1pn We are pleased to share the go...
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My first research paper has been accepted at #NeurIPS2019 Manifold-regression on multivariate timeseries with applications in neuroscience https://t.co/2lgBHbtYd2 Great team work. Thank you @PierreAblin @GaelVaroquaux @agramfort @dngman
arxiv.org
Magnetoencephalography and electroencephalography (M/EEG) can reveal neuronal dynamics non-invasively in real-time and are therefore appreciated methods in medicine and neuroscience. Recent...
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If you do EEG / MEG source localization and you want to leverage your multi-subject data, groupmne ( https://t.co/kS06NeHepN) is for you. Groupmne is a python 🐍 package that relies on @mne_python to process your data for a GroupLasso estimation (and other multi-task models soon.)
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