I am a statistician / data scientist who blogs about nifty sampling methods, which are frequently used in rendering computer graphics such as: ray-tracing (via Quasi-Monte Carlo methods), object placement, dithering, etc...
All these methods try to find the most efficient sampling techniques that minimize various undesirable effects such as aliasing.
Techniques and topics include: blue noise distributions; low discrepancy quasirandom sequences; orthogonal grid-based sampling; and even-sampling on the surface of n-spheres.
My most favourite articles (two of which have previously been featured on HN) include:
Thanks!
To be honest, I hadn't previously made it prominent as I thought RSS had basically died several years ago. However, based on the multiple comments in this parent thread, evidently RSS is still alive and well.
So I'll definitely update my blog now to make it more visible!
http://www.extremelearning.com.au
All these methods try to find the most efficient sampling techniques that minimize various undesirable effects such as aliasing.
Techniques and topics include: blue noise distributions; low discrepancy quasirandom sequences; orthogonal grid-based sampling; and even-sampling on the surface of n-spheres.
My most favourite articles (two of which have previously been featured on HN) include:
* "The unreasonable effectiveness of quasirandom sequences" http://extremelearning.com.au/unreasonable-effectiveness-of-...
* "A new method to construct isotropic blue noise with uniform projections" http://extremelearning.com.au/isotropic-blue-noise-point-set...
* "Evenly distributing points on a sphere" http://extremelearning.com.au/evenly-distributing-points-on-...
I hope that someone finds some of these useful and interesting. ;)