K-means-for-clustering-the-Stars-Typs
simclr
| K-means-for-clustering-the-Stars-Typs | simclr | |
|---|---|---|
| 1 | 13 | |
| 0 | 3,949 | |
| - | 1.4% | |
| 1.8 | 2.9 | |
| over 2 years ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | Apache License 2.0 |
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K-means-for-clustering-the-Stars-Typs
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K means clustering practical project
Hi all of you, I have started leaning Unsupervised learning techniques, and I ve done this simply project cloud you just look at it and give me your feedback about it please 🙃👋 simple Kmeans starting
simclr
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Positive and Negative Sampling Strategies for Representation Learning in Semantic Search
For visual representations, you could look into SimCLR and MoCo. https://github.com/google-research/simclr https://github.com/facebookresearch/moco
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[D] Why is random cropping necessary in SimCLR?
Yeah I think so, it's not hard to check https://github.com/google-research/simclr/blob/2fc637bdd6a723130db91b377ac15151e01e4fc2/data_util.py
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[R] Deep Learning with a Small Training Batch (or Lack Thereof). Part 1
Code for https://arxiv.org/abs/2006.10029 found: https://github.com/google-research/simclr
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[D] Current trends in computer vision related to unsupervised learning
SimCLR v2.0 - https://arxiv.org/abs/2006.10029
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Self-Supervised Contrastive Learning model for video dataset?
My data consists of binary labels (normal & anomalous) where the videos are already broken up into frames in the directory, I'm looking for a model where I can feed a normal-labeled video alongside an anomalous-labeled video like visualized in this example from the SimCLR Repo, a dog will represent the normal video and the chair the anomalous video.
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[P] Choosing a self-supervised learning framework that's easy to use
No, go to the "tf2" folder in the repo root. https://github.com/google-research/simclr/tree/master/tf2
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[D] What is meant by width in the SimCLRv2 paper?
Code for https://arxiv.org/abs/2006.10029 found: https://github.com/google-research/simclr
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[D] Funding PhD in Europe
[1] https://github.com/google-research/simclr [2] https://www.tensorflow.org/tfrc?hl=en&authuser=2
What are some alternatives?
swav - PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882
Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
SimCLR - PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
torchlars - A LARS implementation in PyTorch
Supervised-Constrastive-Learning-in-TensorFlow-2 - Implements the ideas presented in https://arxiv.org/pdf/2004.11362v1.pdf by Khosla et al. [Moved to: https://github.com/sayakpaul/Supervised-Contrastive-Learning-in-TensorFlow-2]
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
moco - PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
soft-vc - Soft speech units for voice conversion