2 papers
stat.CO2024
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms
Måns Magnusson, Jakob Torgander, Paul-Christian Bürkner +3
The generality and robustness of inference algorithms is critical to the success of widely used probabilistic programming languages such as Stan, PyMC, Pyro, and Turing.jl. When de…
cs.LG2024
Hierarchical Bayesian Crowdsourcing with Item Difficulty
Seong Woo Han, Ozan Adıgüzel, Bob Carpenter
In applied statistics and machine learning, the gold standards used for training are often biased and almost always noisy. Dawid and Skene's justifiably popular crowdsourcing model…