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Pyro effect-handler probabilistic programming

Embeds dynamic probabilistic models in Python/PyTorch with sample/parameter primitives and composable Poutine effect handlers, supporting scalable approximate inference.

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Embeds dynamic probabilistic models in Python/PyTorch with sample/parameter primitives and composable Poutine effect handlers, supporting scalable approximate inference.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Universal language expressivity does not make arbitrary posterior inference tractable or exact. Practical stochastic variational inference and user-specified guides are approximate. NUTS, SVI, automatic differentiation and effect-handler concepts are inherited; v1's journal header is an unfinished template, not proof of a 2018 journal publication.

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People and systems

Eli Bingham; Jonathan P. Chen; Martin Jankowiak; Fritz Obermeyer; Neeraj Pradhan; Theofanis Karaletsos; Rohit Singh; Paul Szerlip; Paul Horsfall; Noah D. Goodman

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

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English catalogue narrative

Pyro effect-handler probabilistic programming

Embeds dynamic probabilistic models in Python/PyTorch with sample/parameter primitives and composable Poutine effect handlers, supporting scalable approximate inference.

Scientific scope

Universal language expressivity does not make arbitrary posterior inference tractable or exact. Practical stochastic variational inference and user-specified guides are approximate. NUTS, SVI, automatic differentiation and effect-handler concepts are inherited; v1's journal header is an unfinished template, not proof of a 2018 journal publication.

Reading status

This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.

People and systems

Eli Bingham; Jonathan P. Chen; Martin Jankowiak; Fritz Obermeyer; Neeraj Pradhan; Theofanis Karaletsos; Rohit Singh; Paul Szerlip; Paul Horsfall; Noah D. Goodman

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

Original sources