Alexandre Gramfort
@agramfort
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Building the future of neural interfaces from EMG signals at Meta Reality Labs. Ex Research director at Inria, scikit-learn co-founder, mne-python creator.
Paris, France
Joined July 2007
RT @RFlamary: With some help (and terrifying but so nice code reviews) from @agramfort we made it a proper Python library with a documenta…
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I will be at @NeurIPSConf 2024 in Vancouver next week. Ping me if you want to grab ☕️ or🍺 and chat about ML stuff for biosignals (EMG, EEG, MEG, …)
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RT @seasonedschemer: 1/ We just open-sourced two large wrist electromyography (EMG) datasets - one towards typing without a keyboard and t…
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RT @probabl_ai: ⚠️ Launch Alert 🚀 Today, we're launching the first official and global @scikit_learn practitioner certification program, le…
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🚀 I'm thrilled to share that I've joined a community of proud investors in @probabl_ai, a mission-driven company that is the official brand operator of @scikit_learn, the leading #MachineLearning #OpenSource framework and its 1.5 billion downloads!
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For more details on this work you can read this preprint
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Neuroscience needs a career path for software engineers 👍👍👍
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RT @tomamoral: 🚀 Exciting News! Benchopt 1.6.0 is here with a ton of new features to make ML benchmarking easier than ever! 🎉 🔗 Changelog:…
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RT @RFlamary: Extremely happy to announce the (alpha) release 0.3.0 of SKADA Scikit Adaptation, a python toolbox for domain adaptation full…
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Great work @apmellot 🙌
🎉 Happy to announce our paper "Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets" is accepted at @eusipco2024! Check it out on arXiv: @AntoineCollas @sylvcheva @dngman @agramfort
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RT @tomamoral: With benchopt, we are trying to make it easy to interact and extend this huge benchmark! We are pushing hard to make it eas…
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RT @JeanRemiKing: Really cool paper from @FabianGloeckle, @syhw et al @AIatMeta showing the importance of learning to predict beyond the ne…
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