pub struct BetheApproximation {
pub max_iterations: usize,
pub tolerance: f64,
pub damping: f64,
}Expand description
Bethe approximation for structured variational inference.
Uses the factor graph structure to define a structured approximation. More accurate than mean-field but still tractable.
The Bethe free energy is: F_Bethe = Σ_α H(b_α) - Σ_i (d_i - 1) H(b_i) - Σ_α <log ψ_α>_b_α
where:
- b_α are factor beliefs (cluster marginals)
- b_i are variable beliefs (node marginals)
- d_i is the degree of variable i
- H is entropy
Fields§
§max_iterations: usizeMaximum iterations
tolerance: f64Convergence tolerance
damping: f64Damping factor for message updates
Implementations§
Source§impl BetheApproximation
impl BetheApproximation
Sourcepub fn new(max_iterations: usize, tolerance: f64, damping: f64) -> Self
pub fn new(max_iterations: usize, tolerance: f64, damping: f64) -> Self
Create with custom parameters.
Sourcepub fn run(&self, graph: &FactorGraph) -> Result<HashMap<String, ArrayD<f64>>>
pub fn run(&self, graph: &FactorGraph) -> Result<HashMap<String, ArrayD<f64>>>
Run Bethe approximation using belief propagation.
Returns variable beliefs (marginals).
Trait Implementations§
Auto Trait Implementations§
impl Freeze for BetheApproximation
impl RefUnwindSafe for BetheApproximation
impl Send for BetheApproximation
impl Sync for BetheApproximation
impl Unpin for BetheApproximation
impl UnwindSafe for BetheApproximation
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T: ?Sized,
impl<T> BorrowMut<T> for Twhere
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fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
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Source§impl<SS, SP> SupersetOf<SS> for SPwhere
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impl<SS, SP> SupersetOf<SS> for SPwhere
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fn from_subset(element: &SS) -> SP
The inclusion map: converts
self to the equivalent element of its superset.