Advanced-Deep-Learning-with-Keras
PyTorch-VAE
Advanced-Deep-Learning-with-Keras | PyTorch-VAE | |
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1 | 5 | |
1,716 | 6,013 | |
0.2% | - | |
0.0 | 0.0 | |
about 1 year ago | 7 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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Advanced-Deep-Learning-with-Keras
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Cannot understand how REINFORCE model is trained
I have understood the concept of REINFORCE algorithm and what policy gradient is. However, when I see the code published by PacktPublishing, I was stuck with it.
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?
AdaVAE - [Preprint] AdaVAE: Exploring Adaptive GPT-2s in VAEs for Language Modeling PyTorch Implementation
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
ALAE - [CVPR2020] Adversarial Latent Autoencoders
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
Speech_driven_gesture_generation_with_autoencoder - This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
qubo-nn - Classifying, auto-encoding and reverse-engineering QUBO matrices
Keras-GAN - Keras implementations of Generative Adversarial Networks.
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)