Published:
The majority of deep generative models proposed in the last few years have broadly fallen under three categories—generative adversarial networks (GANs), variational autoencoders (VAEs), and normalizing flows. There are few others, such as autoregressive models and those based on transformers, but they are much slower to sample. As a result, they are not widely used, particularly when the distribution being modeled is very high-dimensional.
Published:
The majority of deep generative models proposed in the last few years have broadly fallen under three categories—generative adversarial networks (GANs), variational autoencoders (VAEs), and normalizing flows. There are few others, such as autoregressive models and those based on transformers, but they are much slower to sample. As a result, they are not widely used, particularly when the distribution being modeled is very high-dimensional.
Published:
Here’s a little piece on the different pictures of linear least squares I wrote for towardsdatascience. All the code used to generate the plots can be found in this github repo.
Published:
Back in 2016, I took part in a large open-source program called Google Summer of Code or GSoC. Specifically, I worked with an organization called BRL-CAD which specialised in a computer-aided design (CAD) software. Here is the official project page from GSoC archives.
Published:
Here’s a little piece on the different pictures of linear least squares I wrote for towardsdatascience. All the code used to generate the plots can be found in this github repo.
Published:
Here’s a little piece on the different pictures of linear least squares I wrote for towardsdatascience. All the code used to generate the plots can be found in this github repo.
Published:
Back in 2016, I took part in a large open-source program called Google Summer of Code or GSoC. Specifically, I worked with an organization called BRL-CAD which specialised in a computer-aided design (CAD) software. Here is the official project page from GSoC archives.
Published:
Here’s a little piece on the different pictures of linear least squares I wrote for towardsdatascience. All the code used to generate the plots can be found in this github repo.
Published:
Back in 2016, I took part in a large open-source program called Google Summer of Code or GSoC. Specifically, I worked with an organization called BRL-CAD which specialised in a computer-aided design (CAD) software. Here is the official project page from GSoC archives.
Published:
The majority of deep generative models proposed in the last few years have broadly fallen under three categories—generative adversarial networks (GANs), variational autoencoders (VAEs), and normalizing flows. There are few others, such as autoregressive models and those based on transformers, but they are much slower to sample. As a result, they are not widely used, particularly when the distribution being modeled is very high-dimensional.