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.
Graphs are a general language for describing and analyzing entities with relations/interactions.
Implementation of Neural Processes with chainer
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)
Here, I am studying the pionneering paper of VAEs called "Auto-Encoding Variational Bayes" written by Diederik P. Kingma and Max Welling.
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.
The wonderful and illustrative notes on Deep Learning take will take a person from Zero to Hero.
mirror of the MeDIL Python package for causal modeling
This repository contains the PyTorch implementation of the ICCV'17 Paper, "Deep Generative Filter for Motion Deblurring"
XR_AI_PROJECT2022
A Time-series Image Segmentation tool with Semi-Unsupervised Encoders.
Hierarchical generative and regressive machine learning for next generation materials screening
OCR-VQGAN, a discrete image encoder (tokenizer and detokenizer) for figure images in Paper2Fig100k dataset. Implementation of OCR Perceptual loss for clear text-within-image generation. Fork from VQGAN in CompVis/taming-transformers
Implementation of MADE (Masked Autoencoder for Distribution Estimation) with chainer
Code for "Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series" @AAAI2021
Official code repository for the paper: Removing Structured Noise using Diffusion Models
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