Alexandr Kalinin

@alxndrkalinin

Biomedical Image Analysis | PhD in Bioinformatics

Ann Arbor, MI
Vrijeme pridruživanja: travanj 2010.

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  1. Prikvačeni tweet
    27. kol 2019.

    Our paper on Breast Tumor Cellularity Assessment using Deep Neural Networks is accepted at Pre-print: See you in Seoul! Joint work w/

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  2. proslijedio/la je Tweet
    3. velj

    MIT's new CS class teaches you things that all the other classes don't teach you, like... 🖥️Shell tools and scripting 🖥️Vim 🖥️Data wrangling 🖥️Command-line environment 🖥️Version control Watch all 11 lectures for free here:

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  3. 4. velj

    Top Trends in Graph in 2020 - better theoretical understanding of GNN - new cool applications of GNN - knowledge graphs are getting popular - new frameworks for graph embeddings

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  4. 4. velj

    ZIDAS 2019 last summer was one of the best summer schools I've ever been to (N~7)! People were awesome and we learned a ton. Fantastic opportunity if you're new-ish to bioimage image analysis. Can't recommend enough!

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  5. proslijedio/la je Tweet
    3. velj

    Really excited to publish this Perspective today, open access! A huge project since 2001.

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  6. proslijedio/la je Tweet
    30. sij

    Pandas 1.0 is here! * Read the release notes: * Read the blogpost reflecting on what 1.0 means to our project: * Install with conda / PyPI: Thanks to our 300+ contributors to this release.

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  7. proslijedio/la je Tweet
    31. sij

    Why Random Forests can’t predict trends and how to overcome this problem. by

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  8. 31. sij

    "Self-Driving Research in Review: NeurIPS 2019" – short reviews of papers from Machine Learning for Autonomous Driving Workshop and main conference by and from

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  9. proslijedio/la je Tweet
    28. sij

    New paper: Towards a Human-like Open-Domain Chatbot. Key takeaways: 1. "Perplexity is all a chatbot needs" ;) 2. We're getting closer to a high-quality chatbot that can chat about anything Paper: Blog:

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  10. proslijedio/la je Tweet
    27. sij

    Announcing Minkowski Engine version 0.4 with 3D sparse tensor reconstruction and better coordinate management, and documentation! Please check out

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  11. proslijedio/la je Tweet
    27. stu 2019.

    1/7 We’d like to share something interesting for machine learning in cardiology. We trained a neural network, EchoNet-Dynamic, to interpret videos to trace the left ventricle and estimate ejection fraction. The results are striking:

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  12. proslijedio/la je Tweet
    23. sij

    Google Dataset Search is now officially out of beta. "Dataset Search has indexed almost 25 million of these datasets, giving you a single place to search for datasets & find links to where the data is." Nice work, Natasha Noy and everyone else involved!

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  13. proslijedio/la je Tweet
    21. sij

    Now it works. Let's spatially explore the 2D images! Thanks for tips, ! And Special Kudos to - 3D Ken Burns model is his great work! Here is what happens if you exaggerate this model. And it's amazing.

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  14. proslijedio/la je Tweet
    22. sij

    Our educational paper on visual intuition for influence functions is out in The American Statistician! arXiv PDF: IFs are central to many stat methods and can bridge machine learning with inference, but they're hard to learn (1/2)

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  15. proslijedio/la je Tweet
    22. sij

    FixMatch: focusing on simplicity for semi-supervised learning and improving state of the art (CIFAR 94.9% with 250 labels, 88.6% with 40). Collaboration with Kihyuk Sohn, Nicholas Carlini

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  16. proslijedio/la je Tweet
    14. sij

    Today was a big day for in , w/ a new, dedicated issue that included this very thoughtful review (that I got to review) by and several other articles

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  17. proslijedio/la je Tweet
    15. sij

    v1.4: customizable mobile builds, Distributed Model Parallelism via experimental RPC API, Java Bindings, Chaining LRSchedulers Summary: Release Notes: Last release for Python 2 (bye bye!)

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  18. proslijedio/la je Tweet
    16. sij
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  19. proslijedio/la je Tweet
    14. sij

    By restructuring math expressions as a language, Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems.

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  20. proslijedio/la je Tweet
    14. sij

    "Transfusion: Understanding Transfer Learning for Medical Imaging" - Really interesting paper with Kleinberg and Bengio in the author list (thanks for pointing it out in this also great post )

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  21. proslijedio/la je Tweet
    10. sij

    Very happy to share our latest work accepted at : we prove that a Self-Attention layer can express any CNN layer. 1/5 📄Paper: 🍿Interactive website : 🖥Code: 📝Blog:

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