It has recently been demonstrated that inference methods based on genealogical processes with recombination can uncover past population history in unprecedented detail. However, these methods scale ...

Improving the conduct and reporting of newer methodological approaches Causal inference, the multidisciplinary field focused ...

Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability*, particularly for reasoning and planning (known as System 2 abilities) has been lacking.

The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as ...

This paper describes threats to making valid causal inferences about pandemic impacts on student learning based on cross-year comparisons of average test scores. The paper uses Spring 2021 test score ...

Membership Inference Authors, Creators & Presenters: Zitao Chen (University of British Columbia), Karthik Pattabiraman ...