Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
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Updated
Apr 9, 2024 - Python
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Optimus: the first large-scale pre-trained VAE language model
[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"
VAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.
Generative models (GAN, VAE, Diffusion Models, Autoregressive Models) implemented with Pytorch, Pytorch_lightning and hydra.
moai is a PyTorch-based AI Model Development Kit (MDK) created to improve data-driven model workflows, design and reproducibility.
Pytorch implementation of GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Official PyTorch implementation of A Quaternion-Valued Variational Autoencoder (QVAE).
🤖 | Learning PyTorch through official examples
Dirichlet-Variational Auto-Encoder by PyTorch
Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
Deep Learning And Applied Artificial Intelligence Project 2019/2020 - Molecular Synthesis & Reconstruction
A Variational Autoencoder in PyTorch for the CelebA Dataset
This repository contains code for VAE and CVAE using residual and inverse residual blocks
A new version of world models using Echo-state networks and random weight-fixed CNNs
Pytorch implementation of a Variational Autoencoder (VAE) that learns from the MNIST dataset and generates images of altered handwritten digits.
Codes for paper: CVQVAE: A REPRESENTATION LEARNING METHOD FOR MULTI-OMICS SINGLE CELL DATA INTEGRATION
A collection of research paper implementations in PyTorch
[WIP] RL agent for the SuperTuxKart game.
Pytorch implementation of Gaussian Mixture Variational Autoencoder GMVAE
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