Goodman and colleagues: Church, a language for generative models

What changed

Introduced Church's Lisp-like generative-model semantics, conditioning, memoization and generic inference examples.

Scientific scope

The record is the five-author UAI 2008 paper. It introduces one probabilistic-programming language and examples; it does not originate all probabilistic programming or prove efficient inference for arbitrary programs. The PMLR page is a 2024 reissue of the 2008 proceedings work.

Evidence

The linked sources identify this contribution and its scope. WRS has not independently reconstructed the scientific claims. The record is the five-author UAI 2008 paper. It introduces one probabilistic-programming language and examples; it does not originate all probabilistic programming or prove efficient inference for arbitrary programs. The PMLR page is a 2024 reissue of the 2008 proceedings work.

Contributors

• Noah D. Goodman · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.
• Vikash K. Mansinghka · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.
• Daniel M. Roy · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.
• Keith Bonawitz · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.
• Joshua B. Tenenbaum · SCIENCE: Named source author of the scoped work; individual effort shares are not measured.

• PMLR reissue record for Church
• Stanford author-hosted Church paper

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

Full scientific record · Browse contribution grades · Request a correction