This important study shows a surprising scale-invariance of the covariance spectrum of large-scale recordings in the zebrafish brain in vivo. A convincing analysis demonstrates that a Euclidean random ...

Department of Computer Science, Metropolitan College, Boston University, Boston, MA, United States On the other hand, using MAD offers a direct measure of deviation and is more resilient to outliers.

In a recent paper Ronald Meester and Timber Kerkvliet argue by example that infinite epistemic regresses have different solutions depending on whether they are analyzed with probability functions or ...

Abstract: Non-linear filters consider probability density functions in various non-parametric representations. They often suffer from the curse of dimensionality. Computation of weights over a grid of ...

The rapid evolution of AI and Gen Ai is shaking the legal sector. While law firms are investing in AI to cut costs and boost efficiency, many aren't fully grasping the extent of the transformation ...

Sequential Propagation of Chaos (SPoC) is a recent technique for solving mean-field stochastic differential equations (SDEs) and their associated nonlinear Fokker-Planck equations. These equations ...

In this lab, we will look at building visualizations known as density plots to estimate the probability density for a given set of data.

What Is A Probability Density Function? A probability density function, also known as a bell curve, is a fundamental statistics concept, that describes the likelihood of a continuous random variable ...