PAWS-TF
FunMatch-Distillation
PAWS-TF | FunMatch-Distillation | |
---|---|---|
1 | 1 | |
43 | 79 | |
- | - | |
1.8 | 1.8 | |
almost 3 years ago | over 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | - |
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PAWS-TF
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Semi-Supervised Learning with Paws in TensorFlow
PAWS introduces a way to combine a small fraction of labeled samples with unlabeled ones during the pre-training of vision models. With its simple and unique approach, it sets SOTA in semi-supervised learning that too with far less compute and parameters.
Here's my implementation of PAWS in TensorFlow: https://github.com/sayakpaul/PAWS-TF/
FunMatch-Distillation
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Knowledge distillation with "Function Matching"
There's a notebook on distributed hyperparameter tuning and it's often not included in the public release of an implementation.
What are some alternatives?
Pseudo-Labelling - Pseudo Labelling on MNIST dataset in Tensorflow 2.x
poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)
TFLiteClassification - TensorFlow Lite Image Classification Python Implementation
Practical_RL - A course in reinforcement learning in the wild
TFLitePoseEstimation - TensorFlow Lite Pose Estimation Python Implementation
TFLiteDetection - TensorFlow Lite Object Detection Python Implementation
adanet - Fast and flexible AutoML with learning guarantees.
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.