feat: bound causal discovery and dense evaluation - #1
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Add context-aware PC/FCI and bootstrap entry points, explicit CI-test and resample budgets, and diagnostics that make bounded searches auditable without returning partial graphs. Reject overflowing or over-budget dense state spaces before allocation, preserve the existing entry points through compatible wrappers, and document the data-regime boundaries that distinguish time-series methods from iid discovery. Harden CI with pinned analyzers, cross-platform tests, coverage and fuzz gates. Prepare the changelog and package metadata for v0.14.0. Co-Authored-By: OpenAI Codex <noreply@openai.com>
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Add context-aware PC/FCI and bootstrap entry points, explicit CI-test and resample budgets, and diagnostics that make bounded searches auditable without returning partial graphs.
Reject overflowing or over-budget dense state spaces before allocation, preserve the existing entry points through compatible wrappers, and document the data-regime boundaries that distinguish time-series methods from iid discovery.
Harden CI with pinned analyzers, cross-platform tests, coverage and fuzz gates. Prepare the changelog and package metadata for v0.14.0.
Co-Authored-By: OpenAI Codex noreply@openai.com