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Methods Wiki — Index

Top-level navigation. See AGENTS.md for the schema and how the assistant should use this wiki.

Start here

  • [[bayesian-inference]] — likelihoods, priors, posteriors, evidence.
  • [[model-comparison]] — Bayes factors, AIC/BIC, posterior predictive checks.
  • [[expectation-propagation]] — factor graphs, message passing, PyAutoFit's graphical/ EP framework; 2026 audit findings.

Samplers

  • [[sampler-candidate-curation]] — bounded source-backed shortlist and on-demand public-provenance handoff to Insight; no scheduled scan.

  • [[mcmc-samplers]] — Metropolis-Hastings, ensemble samplers, Eryn.

  • [[hamiltonian-monte-carlo]] — NUTS, BlackJAX, NumPyro, Stan; gradients via JAX.

  • [[nested-sampling]] — MultiNest, PolyChord, dynesty, UltraNest.

  • [[gpu-nested-sampling]] — JAX-accelerated nested sampling (NSS); vmap batching, chunked vmap.

  • [[initialization-chaining]] — which samplers provide vs require starting points; PyAutoFit chained searches.

  • [[sampler-benchmarks]] — benchmark methodology, historical minimal + A100 results, and pointers to Insight's search campaigns and the project-owned catalogue.

  • [[gradient-optimizer-benchmarks]] — JAX MAP/optimization study on the MGE lens likelihood (CPU + A100): diversity × gradients; multi-start Adam scales (GIGA-Lens), SVGD reaches truth, CMA-ES collapses.

Likelihood-free inference

  • [[simulation-based-inference]] — SBI, ABC, neural ratio estimators.
  • [[neural-posterior-estimation]] — nbi, sbi, lampe, LtU-ILI.
  • [[likelihood-emulation]] — neural likelihood surrogates.

Probabilistic programming

  • [[probabilistic-programming]] — PPL philosophy, conjugate vs MCMC vs NPE.
  • [[message-passing]] — graphical models, belief propagation.

Deep learning

  • [[deep-learning-astro]] — CNNs, BNNs, transformers in astrophysics.
  • [[active-learning]] — accelerated Bayesian inference via surrogates.
  • [[neural-emulators]] — emulating cosmology / N-body / lensing.

Linear algebra & numerics

  • [[linear-inversion]] — least-squares with regularisation.
  • [[gaussian-linear-models]] — closed-form Bayesian linear inference.
  • [[nufft]] — non-uniform fast Fourier transform.
  • [[jax-finufft]] — GPU-accelerated NUFFT.
  • [[autodiff-implicit-diff]] — automatic / implicit differentiation through solvers.

Software ecosystem

  • [[jax-ecosystem]] — Equinox, Optimistix, BlackJAX, NumPyro, …
  • [[aggregator-performance]] — PyAutoFit result loading at catalogue scale: 2026-07 profiling campaign, sqlite verdict, deserialization floor, bugs found by realistic mock data.
  • [[pyautofit]] (cross-link to ../lensing/) — model-fitting framework underlying PyAutoLens.
  • [[scientific-software]] — general-purpose tooling.

Simulation

  • [[forward-modelling]] — full forward-model pipelines.
  • [[hierarchical-population-models]] — multi-level Bayesian inference.

Named entities

  • Samplers / codes: [[polychord]], [[multinest]], [[dynesty]], [[ultranest]], [[nautilus]], [[emcee]], [[blackjax]], [[numpyro]], [[stan]], [[pymc]], [[eryn]], [[nbi]], [[lampe]], [[ltu-ili]].
  • JAX tooling: [[optimistix]], [[equinox]], [[jaxopt]], [[jaxns]].
  • Astro-method codes: [[pyautofit]], [[pylops]], [[finufft]], [[pynufft]].

Sources (bibliography by topic)

These pages describe claim support. Canonical citation metadata and key-management rules live in ../../bibliography/.

  • [[sources-bayesian-inference]]
  • [[sources-samplers]]
  • [[sources-likelihood-free-inference]]
  • [[sources-probabilistic-programming]]
  • [[sources-linear-algebra]]
  • [[sources-nufft]]
  • [[sources-scientific-software]]
  • [[sources-simulations]]
  • Seed (unverified imports): [[seed-deep-learning-methods]], [[seed-medical-imaging-adjacents]] — filename-inferred stubs from the 2026-05 PDF import, every entry still reading Canonical BibTeX key: TODO — no unique match found. They live in seed/, not sources/, and nothing in them may be cited until the paper itself is verified and the entry promoted into the matching sources/ page.

Meta

  • AGENTS.md — schema and usage rules.
  • [[log]] — compilation history.