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Theano: symbolic differentiation and optimized array compilation

Contribution grade

Scientific-computing compiler infrastructure · Human-designed research method or resource

Reference score190,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Compiled typed NumPy-like symbolic graphs through canonicalization, numerical-stability rewrites, specialization and CPU/GPU code generation, with symbolic differentiation; a later community report documents development.

Scientific scope

Compiled typed NumPy-like symbolic graphs through canonicalization, numerical-stability rewrites, specialization and CPU/GPU code generation, with symbolic differentiation; a later community report documents development. Original2010nine-author paper and2016collective-plus112named report retained as distinct source-specific sets, not112original2010authors. Inherits symbolic algebra, graph rewriting and native compilation. Performance can be slower for tiny inputs and differs by operator/hardware. This is general mathematical computing, not new discoveries in application domains. Reported performance has not been independently rerun by WRS.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Original2010nine-author paper and2016collective-plus112named report retained as distinct source-specific sets, not112original2010authors. Inherits symbolic algebra, graph rewriting and native compilation. Performance can be slower for tiny inputs and differs by operator/hardware. This is general mathematical computing, not new discoveries in application domains. Reported performance has not been independently rerun by WRS.

Contributors

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

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