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jep.28.2.3.pdf
1.6 MB
Big Data: New Tricks for Econometrics #Book @Machine_learn
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
FULLTEXT01.pdf
1.1 MB
Application of Machine Learning to Financial Trading
MICHAL HOREMUZ #book
@Machine_learn
✔️ 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

@Machine_learn
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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

@Machine_learn
⬆️ 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

@Machine_learn
2025/07/04 09:51:27
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