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djalil.chafai.net | ||
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mkatkov.wordpress.com
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| | | | | For probability space $latex (\Omega, \mathcal{F}, \mathbb{P})$ with $latex A \in \mathcal{F}$ the indicator random variable $latex {\bf 1}_A : \Omega \rightarrow \mathbb{R} = \left\{ \begin{array}{cc} 1, & \omega \in A \\ 0, & \omega \notin A \end{array} \right.$ Than expected value of the indicator variable is the probability of the event $latex \omega \in... | |
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fabricebaudoin.blog
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| | | | | In this lecture, we studySobolev inequalities on Dirichlet spaces. The approach we develop is related to Hardy-Littlewood-Sobolev theory The link between the Hardy-Littlewood-Sobolev theory and heat kernel upper bounds is due to Varopoulos, but the proof I give below I learnt it from my colleague RodrigoBañuelos. It bypasses the Marcinkiewicz interpolation theorem,that was originally used... | |
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gill1109.com
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| | | | | Abstract and slides of a talk to be given at the IMS conference in London, 27-30 June 2022, https://www.imsannualmeeting-london2022.com/ It has long been realized that the mathematical core of Bell's theorem is essentially a classical probabilistic proof that a certain distributed computing task is impossible: namely, the Monte Carlo simulation of certain iconic quantum correlations.... | |
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www.reedbeta.com
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| | | When you read BRDF theory papers, you'll often see mention of slope space. Sometimes, components of the BRDF such as NDFs or masking-shadowing functions are defined in slope space, or operations are done in slope space before being converted back to ordinary vectors or polar coordinates. However, the meaning and intuition of slope space is rarely explained. Since it may not be obvious exactly what slope space is, why it is useful, or how to transform things to and from it, I thought I would write down a ... | ||
