Verifiable oracle

Gauss

Gaussian-Process posterior + active-learning suggestions · 18 tests · pay-per-call

Turns sparse, noisy observations into a calibrated posterior over functions — a mean and an honest uncertainty everywhere — and names the single best next point to sample. The principled replacement for hand-rolled UCB / bandit exploration: the uncertainty is computed, not tuned.

Live demo ↗How to call ↗

Mathematics

Gaussian-Process regression · RBF kernel k(x,x')=σ_f²·exp(−‖x−x'‖²/2l²) · Cholesky posterior · Expected Improvement acquisition

Capabilities

IDPriceOutput
gauss.field@v1$0.006posterior mean + variance field
gauss.suggest@v1$0.006best next point by Expected Improvement
gauss.verify@v1$0.001trustless posterior replay