tensorlogic_scirs_backend::probabilistic::variational

Struct VariationalInference

pub struct VariationalInference;

Expand description

Entry-point for black-box mean-field variational inference.

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impl VariationalInference

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pub fn fit( log_prob: impl Fn(&[f64]) -> f64, dim: usize, config: VariationalConfig, ) -> TlBackendResult<MeanFieldGaussian>

Fit a mean-field Gaussian posterior q(z) to the log-joint log_prob.

§Arguments

log_prob — evaluates log p(z) at a given z (up to a constant)
dim — number of latent dimensions
config — algorithm hyper-parameters

§Algorithm

Uses Adam (β₁=0.9, β₂=0.999, ε=1e-8) to maximise the ELBO. Gradients of the expected log-joint are estimated by the reparameterisation trick with central finite differences (h=1e-5) for ∂log_p/∂z.

§Errors

Returns an error if dim == 0.

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impl UnwindSafe for VariationalInference

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