gpu-jupyter
PyTorch-VAE
gpu-jupyter | PyTorch-VAE | |
---|---|---|
2 | 5 | |
671 | 6,154 | |
1.5% | - | |
7.8 | 0.0 | |
2 months ago | about 1 month ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | Apache License 2.0 |
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gpu-jupyter
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Mac users, help
Anaconda3 is fine. You probably won't mess anything up, but if you are really concerned, I recommend using Docker for your notebooks. There is even a GPU Jupyter, but I haven't used.
- Suggestions to get gpu-jupyter running on my GPU under Linux
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?
nvidia-container-toolkit - Build and run containers leveraging NVIDIA GPUs
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
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
qubo-nn - Classifying, auto-encoding and reverse-engineering QUBO matrices
disentangling-vae - Experiments for understanding disentanglement in VAE latent representations
torch-metrics - Metrics for model evaluation in pytorch
benchmark_VAE - Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Amortized-SVGD-GAN - Learning to draw samples: with application to amortized maximum likelihood estimator for generative adversarial learning
Advanced-Deep-Learning-with-Keras - Advanced Deep Learning with Keras, published by Packt
minimal_VAE_on_Mario - A minimal VAE trained on Super Mario Bros levels.
vae-anomaly-detector - Experiments on unsupervised anomaly detection using variational autoencoder. The variational autoencoder is implemented in Pytorch.