3 citations · 13 across the 8 of their papers we have counts for
3 papers · 1 filter
Scaling Integer Arithmetic in Probabilistic Programs
William X. Cao, Poorva Garg, Ryan Tjoa +3
Distributions on integers are ubiquitous in probabilistic modeling but remain challenging for many of today's probabilistic programming languages (PPLs). The core challenge comes f…
On the Relationship Between Probabilistic Circuits and Determinantal Point Processes
Honghua Zhang, Steven Holtzen, Guy Van den Broeck
Scaling probabilistic models to large realistic problems and datasets is a key challenge in machine learning. Central to this effort is the development of tractable probabilistic m…
Generating and Sampling Orbits for Lifted Probabilistic Inference
Steven Holtzen, Todd Millstein, Guy Van den Broeck
A key goal in the design of probabilistic inference algorithms is identifying and exploiting properties of the distribution that make inference tractable. Lifted inference algorith…