pytask
PyTorch-VAE
pytask | PyTorch-VAE | |
---|---|---|
1 | 5 | |
101 | 6,054 | |
5.0% | - | |
9.2 | 0.0 | |
7 days ago | 10 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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pytask
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?
EvalAI - :cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
disentangling-vae - Experiments for understanding disentanglement in VAE latent representations
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
torch-fidelity - High-fidelity performance metrics for generative models in PyTorch
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
benchmark_VAE - Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
qubo-nn - Classifying, auto-encoding and reverse-engineering QUBO matrices
torch-metrics - Metrics for model evaluation in pytorch
Amortized-SVGD-GAN - Learning to draw samples: with application to amortized maximum likelihood estimator for generative adversarial learning