LIMoE: Learning Multiple Modalities with One Sparse Mixture of Experts Model
http://ai.googleblog.com/2022/06/limoe-learning-multiple-modalities-with.html
@Machine_learn
  
  http://ai.googleblog.com/2022/06/limoe-learning-multiple-modalities-with.html
@Machine_learn
research.google
  
  LIMoE: Learning Multiple Modalities with One Sparse Mixture-of-Experts Model
  Posted by Basil Mustafa, Research Software Engineer and Carlos Riquelme, Research Scientist, Google Research, Brain team Sparse models stand out am...
❤1
  UniSRec
The proposed approach utilizes the associated description text of items to learn transferable representations across different recommendation scenarios.
Github: https://github.com/rucaibox/unisrec
Paper: https://arxiv.org/abs/2206.05941v1
Google Drive: https://drive.google.com/drive/folders/1Uik0fMk4oquV_bS9lXTZuExAYbIDkEMW?usp=sharing
@Machine_learn
The proposed approach utilizes the associated description text of items to learn transferable representations across different recommendation scenarios.
Github: https://github.com/rucaibox/unisrec
Paper: https://arxiv.org/abs/2206.05941v1
Google Drive: https://drive.google.com/drive/folders/1Uik0fMk4oquV_bS9lXTZuExAYbIDkEMW?usp=sharing
@Machine_learn
❤1👍1
  يكي از مهم ترين چالش هاي طبقه بندي سند اين كه مدل ها به صورت ٢ بعدي به متن و طبقه بندي ان مي پردازند، در واقع مكان قرار گيري جمله در سند كاملا ناديده گرفته ميشه. در اين مقاله ساختار تنسور سه بعدي را پيشنهاد دادم كه جملات در سند، كلمات در جملات و بردار تعبيه شده ي ان ها را در نظر ميگيره. 
به زودي فايل كامل مقاله رو در كانال ميزارم و تقريبا فرايند ثبتش تموم شده.
@Raminmousa
به زودي فايل كامل مقاله رو در كانال ميزارم و تقريبا فرايند ثبتش تموم شده.
@Raminmousa
❤1
  Identifying Disfluencies in Natural Speech
http://ai.googleblog.com/2022/06/identifying-disfluencies-in-natural.html
@Machine_learn
  
  http://ai.googleblog.com/2022/06/identifying-disfluencies-in-natural.html
@Machine_learn
research.google
  
  Identifying Disfluencies in Natural Speech
  Posted by Dan Walker and Dan Liebling, Software Engineers, Google Research People don’t write in the same way that they speak. Written language is ...
  DEEP LEARNING INTERVIEWS REAL-WORLD DEEP LEARNING INTERVIEW PROBLEMS & SOLUTIONS
#book #DL
book
@Machine_learn
link: https://arxiv.org/pdf/2201.00650.pdf
  #book #DL
book
@Machine_learn
link: https://arxiv.org/pdf/2201.00650.pdf
Enabling Creative Expression with Concept Activation Vectors
http://ai.googleblog.com/2022/07/enabling-creative-expression-with.html
@Machine_learn
  
  http://ai.googleblog.com/2022/07/enabling-creative-expression-with.html
@Machine_learn
research.google
  
  Enabling Creative Expression with Concept Activation Vectors
  Posted by Been Kim, Research Scientist, Google Research, Brain Team, and Alison Lentz, Senior Staff Strategist, Google Research, Mural Team Advance...
  👁🗨 CVNets: A library for training computer vision networks
Improved model, MobileViTv2, is state-of-the-art on several mobile vision tasks, including ImageNet object classification and MS-COCO object detection.
Github: https://github.com/apple/ml-cvnets
Examples: https://github.com/apple/ml-cvnets/blob/main/docs/source/en/models
Paper: https://arxiv.org/abs/2206.02680v1
Dataset: https://paperswithcode.com/dataset/coco
@Machine_learn
  
  
  
  
  
Improved model, MobileViTv2, is state-of-the-art on several mobile vision tasks, including ImageNet object classification and MS-COCO object detection.
Github: https://github.com/apple/ml-cvnets
Examples: https://github.com/apple/ml-cvnets/blob/main/docs/source/en/models
Paper: https://arxiv.org/abs/2206.02680v1
Dataset: https://paperswithcode.com/dataset/coco
@Machine_learn
❤4👍1
  Contextual Rephrasing in Google Assistant
http://ai.googleblog.com/2022/05/contextual-rephrasing-in-google.html
@Machine_learn
  
  http://ai.googleblog.com/2022/05/contextual-rephrasing-in-google.html
@Machine_learn
research.google
  
  Contextual Rephrasing in Google Assistant
  Posted by Aurelien Boffy, Senior Staff Software Engineer, and Roberto Pieraccini, Engineering Director, Google Assistant When people converse with ...
  murenei_natural-language-processing-with-python-and-nltk.pdf
    54.2 KB
  Natural Language Processing with Python & nltk Cheat Sheet #Cheat_Sheet @Machine_learn
❤5
  Rewriting Image Captions for Visual Question Answering Data Creation
http://ai.googleblog.com/2022/07/rewriting-image-captions-for-visual.html
@Machine_learn
  
  http://ai.googleblog.com/2022/07/rewriting-image-captions-for-visual.html
@Machine_learn
research.google
  
  Rewriting Image Captions for Visual Question Answering Data Creation
  Posted by Soravit Beer Changpinyo and Doron Kukliansky, Senior Software Engineers, Google Research Visual Question Answering (VQA) is a useful mac...
  This media is not supported in your browser
    VIEW IN TELEGRAM
  Temperature change (1880-2021) 🤯 
@Machine_learn
@Machine_learn
❤11👍1
  🔦 Featurized Query R-CNN
Featurized object queries predicted by a query generation network in the well-established Faster R-CNN framework and develop a Featurized Query R-CN
Github: https://github.com/hustvl/featurized-queryrcnn
Paper: https://arxiv.org/abs/2206.06258v1
Dataset: https://paperswithcode.com/dataset/crowdhuman
@Machine_learn
  
  Featurized object queries predicted by a query generation network in the well-established Faster R-CNN framework and develop a Featurized Query R-CN
Github: https://github.com/hustvl/featurized-queryrcnn
Paper: https://arxiv.org/abs/2206.06258v1
Dataset: https://paperswithcode.com/dataset/crowdhuman
@Machine_learn
GitHub
  
  GitHub - hustvl/Featurized-QueryRCNN: Featurized Query R-CNN
  Featurized Query R-CNN. Contribute to hustvl/Featurized-QueryRCNN development by creating an account on GitHub.
❤1
  Can CNNs Be More Robust Than Transformers?
CNN architectures without any attention-like operations that is as robust as, or even more robust than, Transformers.
Github: https://github.com/ucsc-vlaa/robustcnn
Paper: https://arxiv.org/abs/2206.03452v1
Dataset: https://paperswithcode.com/dataset/imagenet-r
@Machine_learn
  
  
  
  
  
CNN architectures without any attention-like operations that is as robust as, or even more robust than, Transformers.
Github: https://github.com/ucsc-vlaa/robustcnn
Paper: https://arxiv.org/abs/2206.03452v1
Dataset: https://paperswithcode.com/dataset/imagenet-r
@Machine_learn
👍1
  🪁 Age prediction of a speaker's voice
https://miykael.github.io/blog/2022/audio_eda_and_modeling/
@Machine_learn
  https://miykael.github.io/blog/2022/audio_eda_and_modeling/
@Machine_learn
🎯 Object-Compositional Neural Implicit Surfaces
Github: https://github.com/qianyiwu/objsdf
Paper: https://arxiv.org/abs/2207.09686v1
Project: https://qianyiwu.github.io/objectsdf/
Dataset: https://paperswithcode.com/dataset/scannet
@Machine_learn
  Github: https://github.com/qianyiwu/objsdf
Paper: https://arxiv.org/abs/2207.09686v1
Project: https://qianyiwu.github.io/objectsdf/
Dataset: https://paperswithcode.com/dataset/scannet
@Machine_learn