Featdepth
This is the offical codes for the methods described in the "Feature-metric Loss for Self-supervised Learning of Depth and Egomotion".
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Awesome Vaes | 448 | 3 years ago | ||||||||
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| Representation learning for link prediction within social networks | ||||||||||
| Variational Ladder Autoencoder | 198 | 6 years ago | 1 | Python | ||||||
| Implementation of VLAE | ||||||||||
| Codeslam | 146 | 2 years ago | Python | |||||||
| Implementation of CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM paper (https://arxiv.org/pdf/1804.00874.pdf) | ||||||||||
| Featdepth | 143 | 3 years ago | 5 | mit | Python | |||||
| This is the offical codes for the methods described in the "Feature-metric Loss for Self-supervised Learning of Depth and Egomotion". | ||||||||||
| Kate | 130 | 4 years ago | 4 | bsd-3-clause | Python | |||||
| Code & data accompanying the KDD 2017 paper "KATE: K-Competitive Autoencoder for Text" | ||||||||||
| Srl Zoo | 98 | 5 years ago | 1 | mit | Python | |||||
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| Disent | 87 | a year ago | 34 | November 07, 2022 | 14 | mit | Python | |||
| 🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib | ||||||||||
| Desom | 84 | 4 months ago | Python | |||||||
| :globe_with_meridians: Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization | ||||||||||
| Deep Learning For Clustering In Bioinformatics | 62 | 3 years ago | other | Jupyter Notebook | ||||||
| Deep Learning-based Clustering Approaches for Bioinformatics | ||||||||||
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