Generative adversarial networks (GAN) in a reduced-order model (ROM) framework for time series prediction, data assimilation and uncertainty quantification

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Python implementation of the CHIP network model, published in NeurIPS 2020.

In this repository, we focus on the compression of images and video (sequence of image frames) using deep generative models and show that they achieve a better performance in compression ratio and perceptual quality. We explore the use of GANs for this task.

Fast Neural Style Transfer implemented in Tensorflow 2

In this repository, we focus on the compression of images and video (sequence of image frames) using deep generative models and show that they achieve a better performance in compression ratio and perceptual quality. We explore the use of VAEGANs for this task.

Code for the paper: "Simulation-Based Inference with Generative Neural Networks via Scoring Rule Minimization"

I built a Denoising Autoencoder to remove noise from the image. Image Denoising is the process of removing noise from the Images The noise present in the images may be caused by various intrinsic or extrinsic conditions which are practically hard to deal with. The problem of Image Denoising is a very fundamental challenge in the domain of Image …

Variational Autoencoders implementation in Keras.

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