Machine Learning for Mechanical Ventilation Control
https://ai.googleblog.com/2022/02/machine-learning-for-mechanical.html
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  https://ai.googleblog.com/2022/02/machine-learning-for-mechanical.html
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research.google
  
  Machine Learning for Mechanical Ventilation Control
  Posted by Daniel Suo, Software Engineer and Elad Hazan, Research Scientist, Google Research, on behalf of the Google AI Princeton Team   Mechanical...
  Abstract: SuperpixelGridMasks. It is a data augmentation approach which permits to generate various complementary images from original sensor-based data of varied natures e.g. X-Ray scans, vehicular scenes, people images (see data samples). This approach allows to increase the size of your image-based training datasets towards expecting better performances in your analysis tasks. Experiments have shown that the approach can be efficient for image classification tasks.
Link: https://www.researchgate.net/publication/360062941_SuperpixelGridCut_SuperpixelGridMean_and_SuperpixelGridMix_Data_Augmentation
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Link: https://www.researchgate.net/publication/360062941_SuperpixelGridCut_SuperpixelGridMean_and_SuperpixelGridMix_Data_Augmentation
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  FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours
Github: https://github.com/hpcaitech/fastfold
Paper: https://arxiv.org/abs/2203.00854v1
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  Github: https://github.com/hpcaitech/fastfold
Paper: https://arxiv.org/abs/2203.00854v1
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Uncertainty Estimation for Heatmap-based Landmark Localization
Github: https://github.com/pykale/pykale
Documentatuin: https://github.com/pykale/pykale
Paper: https://arxiv.org/abs/2203.02351v1
Dataset: https://paperswithcode.com/dataset/kitti
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  Github: https://github.com/pykale/pykale
Documentatuin: https://github.com/pykale/pykale
Paper: https://arxiv.org/abs/2203.02351v1
Dataset: https://paperswithcode.com/dataset/kitti
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https://web.njit.edu/~ym329/dlg_book/dlg_book.pdf
Deep Learning on Graphs
📖 Book
#deeplearning #DL
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  Deep Learning on Graphs
📖 Book
#deeplearning #DL
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1-s2.0-S154461232100218X-main.pdf
    1.8 MB
  Cryptocurrency liquidity and volatility interrelationships during
the COVID-19 pandemic #Paper @Machine_learn
the COVID-19 pandemic #Paper @Machine_learn
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  2109.12142.pdf
    4.1 MB
  Periodicity in Cryptocurrency Volatility and Liquidity #Paper @Machine_learn
  Alpa: Automated Model-Parallel Deep Learning
https://ai.googleblog.com/2022/05/alpa-automated-model-parallel-deep.html
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  https://ai.googleblog.com/2022/05/alpa-automated-model-parallel-deep.html
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research.google
  
  Alpa: Automated Model-Parallel Deep Learning
  Posted by Zhuohan Li, Student Researcher, Google Research, and Yu Emma Wang, Senior Software Engineer, Google Core    Update — 2022/05/06: This pos...
  Pix2Seq: A New Language Interface for Object Detection
https://ai.googleblog.com/2022/04/pix2seq-new-language-interface-for.html
@Machine_learn
  
  https://ai.googleblog.com/2022/04/pix2seq-new-language-interface-for.html
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research.google
  
  Pix2Seq: A New Language Interface for Object Detection
  Posted by Ting Chen and David Fleet, Research Scientists, Google Research, Brain Team Object detection is a long-standing computer vision task that...
  🔎 Cross-view Transformers for real-time Map-view Semantic Segmentation
Code: https://github.com/bradyz/cross_view_transformers
Paper: https://arxiv.org/abs/2205.02833v1
Dataset: https://paperswithcode.com/dataset/nuscenes
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  Code: https://github.com/bradyz/cross_view_transformers
Paper: https://arxiv.org/abs/2205.02833v1
Dataset: https://paperswithcode.com/dataset/nuscenes
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Predicting_academic_performance.pdf
    900.3 KB
  Predicting academic performance by considering student heterogeneity  #Paper   @Machine_learn
  chapter 5.pdf
    2.5 MB
  Automatic Interpretation of
Carotid Intima–Media
Thickness Videos Using
Convolutional Neural
Networks #Chapter5 @Machine_learn
  Carotid Intima–Media
Thickness Videos Using
Convolutional Neural
Networks #Chapter5 @Machine_learn
chapter 6.pdf
    1.4 MB
  Deep Cascaded Networks for
Sparsely Distributed Object
Detection from Medical
Images #Chapter6 @Machine_learn
Sparsely Distributed Object
Detection from Medical
Images #Chapter6 @Machine_learn
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