Investigating interference or spillover effects among units is a central task in many social science problems. Network experiments are powerful tools for this task, which avoids endogeneity by ...

A comparative study evaluates link prediction, hyperlink prediction and ERGM estimation for inferring missing connections in ...

Former Juniper Networks CTO Raj Yavatkar has unveiled his next endeavor: a startup building silicon focused entirely on inference. Dubbed Ludwig Computing, the upstart is designing “probability-native ...

Machine-learning inference started out as a data-center activity, but tremendous effort is being put into inference at the edge. At this point, the “edge” is not a well-defined concept, and future ...

As AI workloads shift from centralized training to distributed inference, the network faces new demands around latency requirements, data sovereignty boundaries, model preferences, and power ...

The economics of artificial intelligence (AI) are definitively moving away from AI training towards AI production or inference and the real-time use of AI models. While training often represents huge ...

This course is available on the BSc in Econometrics and Mathematical Economics, Erasmus Reciprocal Programme of Study and Exchange Programme for Students from University of California, Berkeley. This ...