A Deep generative model that can generate art - trained on subreddits of art.
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Updated
Dec 3, 2021 - Python
A Deep generative model that can generate art - trained on subreddits of art.
A StyleGAN based on NVIDIA's paper.
A TensorFlow implementation of "Sequence Modeling with Hierarchical Deep Generative Models with Dual Memory" (published in CIKM2017).
Different types of Generative Adversarial Networks and their applications, training workflow, etc.
FontGenerator is an end-to-end system which generates handwritten characters with some font using conditional Generative Adversarial Network (C-GANs)
Graphs are a general language for describing and analyzing entities with relations/interactions.
A Tensorflow-layer API Implementation of Deep Generative Models (MNIST Examples)
Pipeline to create Paper2Fig dataset, a dataset for text-to-image generation from research papers and figures (e.g., diagrams of architectures or methods in fields like Machine Learning or Computer Vision)
This repository contains the PyTorch implementation of the ICCV'17 Paper, "Deep Generative Filter for Motion Deblurring"
A Time-series Image Segmentation tool with Semi-Unsupervised Encoders.
Hierarchical generative and regressive machine learning for next generation materials screening
Code for "Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series" @AAAI2021
Here, I am studying the pionneering paper of VAEs called "Auto-Encoding Variational Bayes" written by Diederik P. Kingma and Max Welling.
mirror of the MeDIL Python package for causal modeling
Deep generative models in a reinforcement learning framework.
Implementation of MADE (Masked Autoencoder for Distribution Estimation) with chainer
Meet Uber's Pyro - popular framework for probabilistic programming. Learn how to introduce regularization and prior assumptions into a model, at first for a simple use case of Bayesian Linear Regression and later in an introduction to deep generative models with Pyro.
Implementation of Neural Processes with chainer
Application of deep generative model discovers novel and diverse functional peptides against microbial resistance
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