This media is not supported in your browser
    VIEW IN TELEGRAM
  Adversarial Latent Autoencoders (ALAE) not only generate 1024x1024 images with StyleGAN’s quality but also allow to manipulate real-world images in a feed-forward manner. Your move, StyleGAN team!
paper: arxiv.org/abs/2004.04467
code: github.com/podgorskiy/ALAE
@Machine_learn
  paper: arxiv.org/abs/2004.04467
code: github.com/podgorskiy/ALAE
@Machine_learn
@Machine_learn
TFRT: A new TensorFlow runtime
https://blog.tensorflow.org/2020/04/tfrt-new-tensorflow-runtime.html
  TFRT: A new TensorFlow runtime
https://blog.tensorflow.org/2020/04/tfrt-new-tensorflow-runtime.html
@Machine_learn
Combinatorial 3D Shape Generation
via Sequential Assembly
https://arxiv.org/pdf/2004.07414.pdf
https://arxiv.org/abs/2004.07414
  Combinatorial 3D Shape Generation
via Sequential Assembly
https://arxiv.org/pdf/2004.07414.pdf
https://arxiv.org/abs/2004.07414
@Machine_learn
Reinforcement Learning with Augmented Data
https://mishalaskin.github.io/rad
Code: https://github.com/MishaLaskin/rad
Paper: https://arxiv.org/abs/2004.14990
  Reinforcement Learning with Augmented Data
https://mishalaskin.github.io/rad
Code: https://github.com/MishaLaskin/rad
Paper: https://arxiv.org/abs/2004.14990
@Machine_learn
BASNet was already great for salient object detection and background removal.
Repo: https://github.com/NathanUA/U-2-Net
  BASNet was already great for salient object detection and background removal.
Repo: https://github.com/NathanUA/U-2-Net
@Machine_learn
The Best Deep Learning Papers from the ICLR 2020 Conference
https://neptune.ai/blog/iclr-2020-deep-learning
  
  The Best Deep Learning Papers from the ICLR 2020 Conference
https://neptune.ai/blog/iclr-2020-deep-learning
neptune.ai
  
  Blog - neptune.ai
  Blog for ML/AI practicioners with articles about LLMOps. You'll find here guides, tutorials, case studies, tools reviews, and more.
  @Machine_learn
Global explanations for discovering bias in data
Github: https://github.com/agamiko/gebi
Code: https://github.com/AgaMiko/GEBI/blob/master/notebooks/GEBI.ipynb
Paper: https://arxiv.org/abs/2005.02269v1
  Global explanations for discovering bias in data
Github: https://github.com/agamiko/gebi
Code: https://github.com/AgaMiko/GEBI/blob/master/notebooks/GEBI.ipynb
Paper: https://arxiv.org/abs/2005.02269v1
Little Ball of Fur
Little Ball of Fur consists of methods to do sampling of graph structured data
Documentation : https://little-ball-of-fur.readthedocs.io/en/latest/#little-ball-of-fur-documentation
github: https://github.com/benedekrozemberczki/littleballoffur
paper: https://arxiv.org/abs/2005.05257v1
@Machine_learn
  
  Little Ball of Fur consists of methods to do sampling of graph structured data
Documentation : https://little-ball-of-fur.readthedocs.io/en/latest/#little-ball-of-fur-documentation
github: https://github.com/benedekrozemberczki/littleballoffur
paper: https://arxiv.org/abs/2005.05257v1
@Machine_learn
GitHub
  
  GitHub - benedekrozemberczki/littleballoffur: Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX…
  Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020) - benedekrozemberczki/littleballoffur
  @Machine_learn
Short over view of Artificial Neural Networks with examples
Page:
https://www.infinitycodex.in/
  Short over view of Artificial Neural Networks with examples
Page:
https://www.infinitycodex.in/
@Machine_learn
Detecting Emotions with CNN Fusion Models - dair.ai - Medium
https://medium.com/dair-ai/detecting-emotions-with-cnn-fusion-models-b066944969c8
  Detecting Emotions with CNN Fusion Models - dair.ai - Medium
https://medium.com/dair-ai/detecting-emotions-with-cnn-fusion-models-b066944969c8
Mohem.pdf
    4.4 MB
  @Machine_learn    
Modified SEIR and AI prediction of the epidemics trend of
COVID-19 in China under public health interventions
#paper
  Modified SEIR and AI prediction of the epidemics trend of
COVID-19 in China under public health interventions
#paper