Lukas Geiger @_lgeiger
deep learning scientist | astroparticle physicist | software engineer github.com/lgeiger London, England Joined October 2016-
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We made our ultra-fast and ultra-small inference engine for Arm Cortex-M processors even smaller. We now require 49% less RAM for 8-bit MobileNetV2 than TensorFlow Lite for Microcontrollers with Arm’s CMSIS-NN kernels. Read the article here: blog.plumerai.com/2021/10/cortex…
🏆 We built the world’s fastest and most memory-efficient deep learning inference software for Arm Cortex-M microcontrollers 🏆 for both Binarized Neural Networks and for 8-bit deep learning models. blog.plumerai.com/2021/10/cortex…
Our latest paper has been accepted to the #MLSys2021 conference! Congratulations Tom, Arash, Adam, Lukas, Tim, Leon, Jelmer and Koen! We wrote a short blog post about the paper and the importance of Larq Compute Engine: blog.plumerai.com/2021/04/mlsys2…
It was great to see so many people attending our #tinyml webcast earlier this week! In case you missed the event, a recording of the talk is now online along with a short blog post explaining the main takeaways from our presentation: blog.plumerai.com/2021/01/tinyml…
A fascinating talk on binarized neural networks for #tinyml by Lukas of @plumerai is now up at youtube.com/watch?v=f9SNqD…, with slides at tinyml.org/wp-content/upl…
Come join us on Tuesday for our @tinyMLTalks webcast! @_lgeiger will explain how we use 🚀Binarized Neural Networks🚀 to enable real-time deep learning on cheap, low-power edge devices. You can register here: us02web.zoom.us/webinar/regist…
We've released v0.4 of Larq Compute Engine! Some of our internal work optimizing BNN performance on microcontrollers has made its way to mobile and Raspberry Pi, as have a few major architectural improvements. 🚀 Full change log: github.com/larq/compute-e…
We just published blog post about open source tools for #DeepLearning presented at our social event at the @iclr_conf! Shout-out to all the co-authors for their great contributions and efforts. Without your help, this would not have been possible! neptune.ai/blog/iclr-2020… (1/n)
We’ve released Larq Compute Engine v0.3, featuring even faster BNN kernels and support for Python 3.8, TensorFlow 2.2, and Windows in the converter! 🎉 💻 Full release notes: github.com/larq/compute-e… 📚 Docs: docs.larq.dev/compute-engine/
The Larq Compute Engine team pushed out LCE v0.2.1 earlier today—same models, up to 15% lower latency. github.com/larq/compute-e…
The Larq Compute Engine team pushed out LCE v0.2.1 earlier today—same models, up to 15% lower latency. github.com/larq/compute-e… https://t.co/ZNIPlkAbPA
We wrote a blog post about how we’re applying a software 2.0 approach in the new module for state-of-the-art binarized neural networks in Larq Zoo (`zoo.sota`). It also features some exciting improvements across the whole Larq stack: blog.larq.dev/2020/03/larq-e…
We’ve just released Larq v0.9, featuring: 🔲 Non-zero padding 💾 Easier export for binary weights 📋 Improved model summaries And lots more! 🎉 github.com/larq/larq/rele…
More about Larq Compute Engine: 📑 Docs: docs.larq.dev/compute-engine 👩💻 GitHub: github.com/larq/compute-e… 💱 MLIR converter: docs.larq.dev/compute-engine… 📱 Android deployment: docs.larq.dev/compute-engine… 🥧 Raspberry Pi deployment: docs.larq.dev/compute-engine…
Really excited to finally share what we've been working on 🎉
Really excited to finally share what we've been working on 🎉
Our binarized neural network training library, Larq, has been published in the Journal of Open Source Software! 🎉 📄 Read the paper by @_lgeiger et al. here: joss.theoj.org/papers/10.2110… 🔎 Documentation: larq.dev 💻 Code: github.com/larq/larq
Our binarized neural network training library, Larq, has been published in the Journal of Open Source Software! 🎉 📄 Read the paper by @_lgeiger et al. here: joss.theoj.org/papers/10.2110… 🔎 Documentation: larq.dev 💻 Code: github.com/larq/larq
Just published in #JOSS_theOJ: 'Larq: An Open-Source Library for Training Binarized Neural Networks' doi.org/10.21105/joss.…
James, @_lgeiger and @khelwegen had a great time presenting our work on optimizing BNNs at #NeurIPS2019 last week! See our paper, poster, and code here: plumerai.com/neurips19
Want to know more? Come see us Wednesday 10:45am - 12:45pm in East Exhibition Hall B + C, at poster booth #103! neurips.cc/Conferences/20… #NeurIPS #NeurIPS2019 #BNN
Want to know more? Come see us Wednesday 10:45am - 12:45pm in East Exhibition Hall B + C, at poster booth #103! neurips.cc/Conferences/20… #NeurIPS #NeurIPS2019 #BNN
We’ll be @NeurIPSConf in Vancouver next week to present our paper: Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization 📄 Paper: arxiv.org/abs/1906.02107 🖼 Poster: github.com/plumerai/rethi… 💻 Code: github.com/plumerai/rethi…
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