May 14, 2022
«Poison owner” by @geneartor
When you have poison, you have a great temptation to drink it. It's like a gun you want to shoot if you have it. Or is that not everybody's?
seen from Kazakhstan
seen from United States
seen from Mexico
seen from Congo - Brazzaville
seen from United States
seen from Philippines
seen from China
seen from Malaysia
seen from Australia
seen from China
seen from Sweden
seen from Malaysia
seen from Malaysia
seen from Australia
seen from Türkiye
seen from United States
seen from Singapore
seen from Spain
seen from Germany
seen from Ireland
«Poison owner” by @geneartor
When you have poison, you have a great temptation to drink it. It's like a gun you want to shoot if you have it. Or is that not everybody's?
Project Title: VAE with Spatial-Attention and Label-Controlled Generation - Keras-Exercise-091
Here’s a far more advanced Keras project, building on your extensive experience—this time implementing a Variational Autoencoder (VAE) with attention modules on the Fashion-MNIST dataset, and then using it for controlled image generation. The goal is to teach representation learning, disentanglement, and generative modeling with attention. The code comprises ~98% of the content; summary and usage…
Project Title: VAE with Spatial-Attention and Label-Controlled Generation - Keras-Exercise-091
Here’s a far more advanced Keras project, building on your extensive experience—this time implementing a Variational Autoencoder (VAE) with attention modules on the Fashion-MNIST dataset, and then using it for controlled image generation. The goal is to teach representation learning, disentanglement, and generative modeling with attention. The code comprises ~98% of the content; summary and usage…
Project Title: VAE with Spatial-Attention and Label-Controlled Generation - Keras-Exercise-091
Here’s a far more advanced Keras project, building on your extensive experience—this time implementing a Variational Autoencoder (VAE) with attention modules on the Fashion-MNIST dataset, and then using it for controlled image generation. The goal is to teach representation learning, disentanglement, and generative modeling with attention. The code comprises ~98% of the content; summary and usage…
Project Title: VAE with Spatial-Attention and Label-Controlled Generation - Keras-Exercise-091
Here’s a far more advanced Keras project, building on your extensive experience—this time implementing a Variational Autoencoder (VAE) with attention modules on the Fashion-MNIST dataset, and then using it for controlled image generation. The goal is to teach representation learning, disentanglement, and generative modeling with attention. The code comprises ~98% of the content; summary and usage…
Project Title: VAE with Spatial-Attention and Label-Controlled Generation - Keras-Exercise-091
Here’s a far more advanced Keras project, building on your extensive experience—this time implementing a Variational Autoencoder (VAE) with attention modules on the Fashion-MNIST dataset, and then using it for controlled image generation. The goal is to teach representation learning, disentanglement, and generative modeling with attention. The code comprises ~98% of the content; summary and usage…
Project Title: RealNVP Normalizing Flow for Density Estimation - Keras-Exercise-030
""" Project Title: RealNVP Normalizing Flow for Density Estimation (ai-ml-ds-RealNVPMix2025) File Name: realnvp_normalizing_flow.py Short Description: Implements a RealNVP normalizing flow in pure Keras to learn an invertible transformation between a simple base Gaussian and a complex 2D mixture-of-Gaussians target distribution. Includes coupling layers, masking, log‑determinant tracking,…
Project Title: RealNVP Normalizing Flow for Density Estimation - Keras-Exercise-030
""" Project Title: RealNVP Normalizing Flow for Density Estimation (ai-ml-ds-RealNVPMix2025) File Name: realnvp_normalizing_flow.py Short Description: Implements a RealNVP normalizing flow in pure Keras to learn an invertible transformation between a simple base Gaussian and a complex 2D mixture-of-Gaussians target distribution. Includes coupling layers, masking, log‑determinant tracking,…