Ranger - a synergistic optimizer using RAdam (Rectified Adam) and Lookahead in one codebase
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Updated
Aug 23, 2019 - Python
Ranger - a synergistic optimizer using RAdam (Rectified Adam) and Lookahead in one codebase
On The Variance Of The Adaptive Learning Rate And Beyond in tensorflow
MXNet implementation of RAdam optimizer
python code, notebooks and Images used for AI502 Midterm Project.
Quasi Hyperbolic Rectified DEMON Adam/Amsgrad with AdaMod, Gradient Centralization, Lookahead, iterative averaging and decorrelated Weight Decay
Object detection and instance segmentation on MaskRCNN with torchvision, albumentations, tensorboard and cocoapi. Supports custom coco datasets with positive/negative samples.
基于tf.keras的多标签多分类模型
Classify known sites from around the world, given challenging and very big data set. This project is based on a kaggle competition.
RAdam implemented in Keras & TensorFlow
A collection of deep learning models (PyTorch implemtation)
tf-keras-implemented YOLOv2
Pytorch implementation of lookahead optimizer(https://arxiv.org/pdf/1907.08610.pdf) and RAdam(https://arxiv.org/pdf/1908.03265.pdf)
Benchmarking Optimizers for Sign Language detection
Literature survey of convex optimizers and optimisation methods for deep-learning; made especially for optimisation researchers with ❤️
Nadir: Cutting-edge PyTorch optimizers for simplicity & composability! 🔥🚀💻
optimizer & lr scheduler & loss function collections in PyTorch
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