Explore >> Select a destination
|
You are here 
|
www.reedbeta.com | ||
| | | | |
jamie-wong.com
|
|
| | | | | One of the techniques used in many demo scenes is called ray marching. This algorithm, used in combination with a special kind of function called | |
| | | | |
thenumb.at
|
|
| | | | | Or, where does that \(\sin\theta\) come from? Integrating functions over spheres is a ubiquitous task in graphicsand a common source of confusion for beginners. In particular, understanding why integration in spherical coordinates requires multiplying by \(\sin\theta\) takes some thought. The Confusion So, we want to integrate a function \(f\) over the unit sphere. For simplicity, lets assume \(f = 1\). Integrating \(1\) over any surface computes the area of that surface: for a unit sphere, we should end... | |
| | | | |
algassert.com
|
|
| | | | | Craig Gidney's computer science blog | |
| | | | |
blog.keras.io
|
|
| | | [AI summary] The text discusses various types of autoencoders and their applications. It starts with basic autoencoders, then moves to sparse autoencoders, deep autoencoders, and sequence-to-sequence autoencoders. The text also covers variational autoencoders (VAEs), explaining their structure and training process. It includes code examples for each type of autoencoder and mentions the use of tools like TensorBoard for visualization. The VAE section highlights how to generate new data samples and visualize the latent space. The text concludes with references and a note about the potential for further topics. | ||
