jep.28.2.3.pdf
1.6 MB
Big Data: New Tricks for Econometrics #Book @Machine_learn
murenei_natural-language-processing-with-python-and-nltk.pdf
54.2 KB
Natural Language Processing with Python & nltk Cheat Sheet #Cheat_Sheet @Machine_learn
Rewriting Image Captions for Visual Question Answering Data Creation
http://ai.googleblog.com/2022/07/rewriting-image-captions-for-visual.html
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http://ai.googleblog.com/2022/07/rewriting-image-captions-for-visual.html
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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...
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Temperature change (1880-2021) 🤯
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🔦 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
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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
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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.
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
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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
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🪁 Age prediction of a speaker's voice
https://miykael.github.io/blog/2022/audio_eda_and_modeling/
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https://miykael.github.io/blog/2022/audio_eda_and_modeling/
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🎯 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
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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
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Towards Reliability in Deep Learning Systems
http://ai.googleblog.com/2022/07/towards-reliability-in-deep-learning.html
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http://ai.googleblog.com/2022/07/towards-reliability-in-deep-learning.html
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research.google
Towards Reliability in Deep Learning Systems
Posted by Dustin Tran and Balaji Lakshminarayanan, Research Scientists, Google Research Deep learning models have made impressive progress in visio...
✔️ Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case
This library implements some of the most common (Variational) Autoencoder models.
Github: https://github.com/clementchadebec/benchmark_VAE
Paper: https://arxiv.org/abs/2206.08309v1
Dataset: https://paperswithcode.com/dataset/celeba
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This library implements some of the most common (Variational) Autoencoder models.
Github: https://github.com/clementchadebec/benchmark_VAE
Paper: https://arxiv.org/abs/2206.08309v1
Dataset: https://paperswithcode.com/dataset/celeba
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The Complete Collection of Data Science Cheat Sheets
https://www.kdnuggets.com/2022/02/complete-collection-data-science-cheat-sheets-part-2.html
The Complete Collection of Data Science Cheat Sheets - Part 1.
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https://www.kdnuggets.com/2022/02/complete-collection-data-science-cheat-sheets-part-2.html
The Complete Collection of Data Science Cheat Sheets - Part 1.
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⚡️ K-CAI NEURAL API
KCAI NEURAL API Keras based neural network API that will allow you to prototype
Github: https://github.com/joaopauloschuler/k-neural-api
Colab: https://colab.research.google.com/github/joaopauloschuler/k-neural-api/blob/master/examples/jupyter/simple_image_classification_with_any_dataset.ipynb
Paper: https://www.researchgate.net/publication/360226228_Grouped_Pointwise_Convolutions_Reduce_Parameters_in_Convolutional_Neural_Networks
Dataset: https://paperswithcode.com/dataset/plantdoc
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KCAI NEURAL API Keras based neural network API that will allow you to prototype
Github: https://github.com/joaopauloschuler/k-neural-api
Colab: https://colab.research.google.com/github/joaopauloschuler/k-neural-api/blob/master/examples/jupyter/simple_image_classification_with_any_dataset.ipynb
Paper: https://www.researchgate.net/publication/360226228_Grouped_Pointwise_Convolutions_Reduce_Parameters_in_Convolutional_Neural_Networks
Dataset: https://paperswithcode.com/dataset/plantdoc
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⚡️ K-CAI NEURAL API
KCAI NEURAL API Keras based neural network API that will allow you to prototype
Github: https://github.com/joaopauloschuler/k-neural-api
Colab: https://colab.research.google.com/github/joaopauloschuler/k-neural-api/blob/master/examples/jupyter/simple_image_classification_with_any_dataset.ipynb
Paper: https://www.researchgate.net/publication/360226228_Grouped_Pointwise_Convolutions_Reduce_Parameters_in_Convolutional_Neural_Networks
Dataset: https://paperswithcode.com/dataset/plantdoc
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KCAI NEURAL API Keras based neural network API that will allow you to prototype
Github: https://github.com/joaopauloschuler/k-neural-api
Colab: https://colab.research.google.com/github/joaopauloschuler/k-neural-api/blob/master/examples/jupyter/simple_image_classification_with_any_dataset.ipynb
Paper: https://www.researchgate.net/publication/360226228_Grouped_Pointwise_Convolutions_Reduce_Parameters_in_Convolutional_Neural_Networks
Dataset: https://paperswithcode.com/dataset/plantdoc
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📲 Forecasting Future World Events with Neural Networks
Github: https://github.com/andyzoujm/autocast
Paper: https://arxiv.org/abs/2206.15474v1
Dataset: https://people.eecs.berkeley.edu/~hendrycks/intervalqa.tar.gz
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Github: https://github.com/andyzoujm/autocast
Paper: https://arxiv.org/abs/2206.15474v1
Dataset: https://people.eecs.berkeley.edu/~hendrycks/intervalqa.tar.gz
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🎯 A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets and Challenges
Github: https://github.com/shiqiyu/opengait
Paper: https://arxiv.org/abs/2206.13732v1
Dataset: https://paperswithcode.com/dataset/usf
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Github: https://github.com/shiqiyu/opengait
Paper: https://arxiv.org/abs/2206.13732v1
Dataset: https://paperswithcode.com/dataset/usf
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⬆️ YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Github: https://github.com/wongkinyiu/yolov7
Paper: https://arxiv.org/abs/2207.02696v1
Dataset: https://paperswithcode.com/dataset/coco
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YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Github: https://github.com/wongkinyiu/yolov7
Paper: https://arxiv.org/abs/2207.02696v1
Dataset: https://paperswithcode.com/dataset/coco
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