11–20 of 20 posts
I thought that was pretty cool but after reading the article the actual way it was done was much more interesting.
From another post on the site "I researched various different approaches to this problem and implemented the algorithms Conjugate Projected Gradient, Projected Steepest Descent, Projected Gauss-Seidel, Subspace Minimization with Conjugate Gradient, Minimum Residual and Symmetric LQ solvers, as well as Projected Gauss-Seidel with line search using the Armijo rule."
If nothing else whatever field this is from has very fancy sounding jargon. From another post on the site "I researched various different approaches to this problem and implemented the algorithms Conjugate Projected Gradient, Projected Steepest Descent, Projected Gauss-Seidel, Subspace Minimization with Conjugate Gradient, Minimum Residual and Symmetric LQ solvers, as well as Projected Gauss-Seidel with line search u…
Browsing the rest of the website is also recommended. And also very depressing.
If nothing else whatever field this is from has very fancy sounding jargon. From another post on the site "I researched various different approaches to this problem and implemented the algorithms Conjugate Projected Gradient, Projected Steepest Descent, Projected Gauss-Seidel, Subspace Minimization with Conjugate Gradient, Minimum Residual and Symmetric LQ solvers, as well as Projected Gauss-Seidel with line search u…
These are almost all algorithms I've either heard about or actually implemented in a graduate level numerical methods course given in a mechanical engineering department. Nothing extremely esoteric but it depends on your background. I've no clue about most classic CS algorithms (dijkstra, algo for tree structures, etc).
If nothing else whatever field this is from has very fancy sounding jargon. From another post on the site "I researched various different approaches to this problem and implemented the algorithms Conjugate Projected Gradient, Projected Steepest Descent, Projected Gauss-Seidel, Subspace Minimization with Conjugate Gradient, Minimum Residual and Symmetric LQ solvers, as well as Projected Gauss-Seidel with line search u…
I'm always absolutely amazed by people who have both the considerable technical skill and the deep sense of aesthetics required to produce things like this.
Yet if you want to, you can spend the rest of your life figuring out shortcuts and hacks and tweaks to make your rendering faster (to let you zoom further or increase resolution) or to produce things like this video.
It's a lot of fun to play with because you get aesthetic results very easily, yet you can continue to add improve on your results as long as you have patience for.
I'm always absolutely amazed by people who have both the considerable technical skill and the deep sense of aesthetics required to produce things like this.
So say we all.