DeepAI AI Chat
Log In Sign Up

Techreport: Time-sensitive probabilistic inference for the edge

by   Christian Weilbach, et al.

In recent years the two trends of edge computing and artificial intelligence became both crucial for information processing infrastructures. While the centralized analysis of massive amounts of data seems to be at odds with computation on the outer edge of distributed systems, we explore the properties of eventually consistent systems and statistics to identify sound formalisms for probabilistic inference on the edge. In particular we treat time itself as a random variable that we incorporate into statistical models through probabilistic programming.


page 1

page 2

page 3

page 4


Convergence of Edge Computing and Deep Learning: A Comprehensive Survey

Ubiquitous sensors and smart devices from factories and communities guar...

Towards Self-learning Edge Intelligence in 6G

Edge intelligence, also called edge-native artificial intelligence (AI),...

Disaggregated Memory at the Edge

This paper describes how to augment techniques such as Distributed Share...

Mobile Edge Computing for the Metaverse

The Metaverse has emerged as the next generation of the Internet. It aim...