Experimenting with the PPGN-h architecture by adding new discriminators to the layers of the encoder
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Updated
Aug 18, 2018 - Python
Experimenting with the PPGN-h architecture by adding new discriminators to the layers of the encoder
implementation of convolutional VAE in pytorch
Music generation with Wasserstein Autoencoders
📦 Ready to use implementations of state-of-the-art generative models in TensorFlow 2
Re-implemntation of scVI (a deep generative model) using PyTorch, PyTorch Lightning, and Pyro
📦 Ready to use implementations of state-of-the-art generative models in PyTorch
Undersmoothing Causal Estimators with Generative Trees
Generic PyTorch Pipeline for solving Inverse Problems using Score-based Generative Models
Implementing a Denoising Diffsuion Probabilistic Model (DDPM) on Tensorflow from scratch for Pokémon sprites synthesis
Thesis projects
Code for Diff-SCM paper
PyTorch implementation of the RealNVP model
Deep-based generation of Wing Interferential Patterns Images for the surveillance of blood-sucking insect population by Machine learning algorithms(Generative adversarial networks, Adversarial Autoencoders). Summer intership, research project
[ICLR 2022] Toy Experiments for Denoising Likelihood Score Matching for Conditional Score-based Data Generation
A discrete diffusion model that works on graphs and optimized for ELBO computation.
Experimental framework for GAN/VAE research
CFG-GAN: Composite functional gradient learning of generative adversarial models
Using GPT3 to make a horoscope predictor.
Implement and test different types of generative models.
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