I don't remember much about #Markov Chains, #Random-Walk. Fokker-Planck. Jeez Louise. Scratched around trying to read and understand stuff. Fortunately at the time, my advisor cleared the decks, said don't bother, here is a 2-D #Gaussian dispersion model I wrote in BASIC. Re-write it in #FORTRAN and add two flavors: a #Lagrangian and a K-theory particle dispersion model, for a convective boundary layer. Use those formulations for a connective boundary layer you learned in Turbulence.

#statstab #204 GLMMadaptive: Generalized Linear Mixed Models using Adaptive Gaussian Quadrature

Thoughts: No clue what this package is does, but seems useful. Maybe someone can explain some use cases.

#glmm #gaussian #modelling #r #stats

https://drizopoulos.github.io/GLMMadaptive/

Congratulations to @OlivierSupplisson for his beautiful #spatiotemporal analysis of the #seroprevalence of #herpesviruses (#HSV1, #HSV2, #VZV, #EBV, and #CMV in #france

This is massive #data from #CERBA (>300,000 serologies) and beautiful #latent #gaussian #Models in #R-INLA!

https://www.tandfonline.com/doi/full/10.1080/23744235.2024.2365906

(don't hesitate to contact us for PDF versions)

@CirbCdf @cnrs @collegedefrance #inserm

Added a convolution kernel filtering operator for polygons/polylines to https://thi.ng/geom, incl. some useful preset kernels: box filter, triangle, gaussian, all with configurable size...

The image shows effects of various kernel sizes & iterations. Unlike with subdivision smoothing, here each version has the exact same number of vertices, only their positions are impacted: orange = box, magenta = triangle, blue = gaussian

(For now the operator is only implemented for polygons (also w/ holes) & polylines, but can be extended to other shape types...)

'Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees', by Alexander Terenin et al.

http://jmlr.org/papers/v25/22-1170.html

#interpolation #sparse #gaussian

'Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility', by Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron.

http://jmlr.org/papers/v24/22-0537.html

#gaussian #distributions #weigh

So how are these new #gaussian #splats in #gfx different from the splats of two decades ago?

Variational Elliptical Processes

Maria Margareta Bånkestad, Jens Sjölund, Jalil Taghia, Thomas B. Schön

Action editor: Sinead Williamson.

https://openreview.net/forum?id=djN3TaqbdA