There are 2 repositories under deep-generative-models topic.
List of Molecular and Material design using Generative AI and Deep Learning
SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches, CVPR2022
Unofficial PyTorch Implementation of Denoising Diffusion Probabilistic Models (DDPM)
Notebooks for the Practicals at the Deep Learning Indaba 2022.
Materials of the Nordic Probabilistic AI School 2019.
Materials of the Nordic Probabilistic AI School 2021.
Awesome De novo drugs design papers
A deep generative model to predict aircraft actual trajectories using high dimensional weather data
📖 A curated list of resources dedicated to avatar.
A pytorch implementation of the paper "Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control"
A PyTorch Implementation of Convolutional Conditional Neural Process.
Official PyTorch implementation of 🏁 MFCVAE 🏁: "Multi-Facet Clustering Variatonal Autoencoders (MFCVAE)" (NeurIPS 2021). A class of variational autoencoders to find multiple disentangled clusterings of data.
DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations
PyTorch Implementation of V-objective Diffusion Probabilistic Models with Classifier-free Guidance
The official implementation of the manuscript Learning the complexity of urban mobility with deep generative collaboration network.
Code, documentation, and tutorials for the DGD model trained on bulk RNA-Seq data.
Pytorch implementation of WIPA: Super-resolution of very low-resolution face images with a Wavelet Integrated, Identity Preserving, Adversarial Network.
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)
PyTorch Implementations of Popular Deep Generative Models.
A basic PyTorch implementation of the Collaborative Sampling in Generative Adversarial Networks
Official PyTorch implementation of the paper "MultiSpectral diffusion: joint generation of wavelet coefficients for image synthesis and upsampling"
Unofficial PyTorch implementation of IODINE https://arxiv.org/abs/1903.00450
Facial Unpaired Image-to-Image Translation with (Self-Attention) Conditional Cycle-Consistent Generative Adversarial Networks
Exercises from IT3030 V20
Deep Generative Models with clean and well-annotated PyTorch re-implementation
This GitHub repository showcases my bachelor thesis which is focused on exploring the application and comparison of various deep generative models for synthetic image augmentation in manufacturing domain.
Resources and references on solved and unsolved problems in generative AI, covering probabilistic foundations, model architectures, learning algorithms, implementations, and applications.
Denoising Diffusion Probabilistic Models
Deep Generative Models
Mini-project for my CST Part III Representation Learning on Graphs and Networks (L45) module
A Variational Autoencoder (VAE) for face image reconstruction with slight new face generation. Compresses faces into latent space, reconstructs realistic images, and generates subtle variations. Useful for facial synthesis, data augmentation, image compression and generative modeling.
Diffusion model for image generation, based on the Denoising Diffusion Probabilistic Models (DDPM) and U-Net architecture.