torch-metrics
PyTorch-VAE
| torch-metrics | PyTorch-VAE | |
|---|---|---|
| 2 | 5 | |
| 109 | 6,013 | |
| - | - | |
| 1.8 | 0.0 | |
| about 3 years ago | 7 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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torch-metrics
- Torch Metrics Library
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[P] Contributions needed for PyTorch metrics library
Hi all I've created a metrics library for PyTorch here but will need lots of contributions to make it as user friendly as possible. Feature requests/ contributions are welcome :) Feel free to use it in your projects if you find it useful. Thanks.
PyTorch-VAE
- Help with VAE
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Confusions on VAE implementation
I am a beginner in VAE implementation and I am currently going through codes here.
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Confusion regarding Variational AutoEncoder Implementation
I am referring to the code in the link here for VAE code. I have the following questions and confusions:
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How to extract feature from 2 tensors into one? what layer should be used?
Here's a repo that has a large number of VAE variants for Pytorch: https://github.com/AntixK/PyTorch-VAE
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VAEs
Face embedding with VAEs https://github.com/AntixK/PyTorch-VAE
What are some alternatives?
ignite - High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
ALAE - [CVPR2020] Adversarial Latent Autoencoders
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
onemetric - One Metrics Library to Rule Them All!
qubo-nn - Classifying, auto-encoding and reverse-engineering QUBO matrices
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
disentangling-vae - Experiments for understanding disentanglement in VAE latent representations
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
benchmark_VAE - Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)