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searching for Log probability 18 found (31 total)

Stan (software) (901 words) [view diff] exact match in snippet view article

(Bayesian) statistical model with an imperative program calculating the log probability density function. Stan is licensed under the New BSD License. Stan

Gibbs algorithm (251 words) [view diff] exact match in snippet view article find links to article

of microstates of a thermodynamic system by minimizing the average log probability ⟨ ln ⁡ p i ⟩ = ∑ i p i ln ⁡ p i {\displaystyle \langle \ln p_{i}\rangle

Naive Bayes classifier (7,362 words) [view diff] no match in snippet view article find links to article

scaling factor is irrelevant, and it is sufficient to calculate the log-probability up to a factor: ln ⁡ p ( C k ∣ x 1 , … , x n ) = ln ⁡ p ( C k ) + ∑

Generalized least squares (2,846 words) [view diff] no match in snippet view article find links to article

does not depend on b {\displaystyle \mathbf {b} } . Therefore the log-probability is log ⁡ p ( b | ε ) = log ⁡ p ( ε | b ) + ⋯ = − 1 2 ε T Ω − 1 ε +

CYK algorithm (2,189 words) [view diff] no match in snippet view article find links to article

multiplying many probabilities together. This can be dealt with by summing log-probability instead of multiplying probabilities. The worst case running time of

Protein–protein interaction prediction (2,915 words) [view diff] no match in snippet view article find links to article

E-score which measures if two domains interact. It is calculated as log(probability that the two proteins interact given that the domains interact/probability

Boltzmann machine (3,676 words) [view diff] exact match in snippet view article find links to article

distribution that the energy of a state is proportional to the negative log probability of that state) yields: Δ E i = − k B T ln ⁡ ( p i=off ) − ( − k B T

Chinese restaurant process (3,990 words) [view diff] exact match in snippet view article find links to article

to zero as it should. (Practical implementations that evaluate the log probability for partitions via log ⁡ L | B | _ = log ⁡ | Γ ( L + 1 ) | − log ⁡

Power law (8,193 words) [view diff] exact match in snippet view article find links to article

methods are often based on making a linear regression on either the log–log probability, the log–log cumulative distribution function, or on log-binned data

Information content (4,445 words) [view diff] no match in snippet view article find links to article

(a highly improbable outcome is very surprising). This term (as a log-probability measure) was introduced by Edward W. Samson in his 1951 report "Fundamental

Grand canonical ensemble (5,285 words) [view diff] no match in snippet view article find links to article

parameters (fixed V), the grand canonical ensemble average of the log-probability − ⟨ log ⁡ P ⟩ {\displaystyle -\langle \log P\rangle } (also called

Rejection sampling (4,481 words) [view diff] no match in snippet view article find links to article

If it helps, define your envelope distribution in log space (e.g. log-probability or log-density) instead. That is, work with h ( x ) = log ⁡ g ( x )

Directional component analysis (1,917 words) [view diff] exact match in snippet view article find links to article

matrix C {\displaystyle C} . As a function of x {\displaystyle x} , the log probability density is proportional to − x t C − 1 x {\displaystyle -x^{t}C^{-1}x}

Regularized least squares (4,894 words) [view diff] no match in snippet view article find links to article

observe that a normal prior on w {\displaystyle w} centered at 0 has a log-probability of the form log ⁡ P ( w ) = q − α ∑ j = 1 d w j 2 {\displaystyle \log

Free energy principle (6,424 words) [view diff] exact match in snippet view article find links to article

systems minimise a quantity known as surprisal (which is the negative log probability of some outcome); or equivalently, its variational upper bound, called

Mixture of experts (5,651 words) [view diff] no match in snippet view article find links to article

of experts predict that the output is distributed according to the log-probability density function: ln ⁡ f θ ( y | x ) = ln ⁡ [ ∑ i e k i T x + b i ∑

Flow-based generative model (9,377 words) [view diff] no match in snippet view article find links to article

distributions after scaling and translation of the input distributions in log-probability space. For p , q ∈ Δ n − 1 {\displaystyle \mathbf {p} ,\mathbf {q}

High-dimensional Ising model (6,317 words) [view diff] no match in snippet view article find links to article

in H. For any value of the slowly varying field H, the free energy (log-probability) is a local analytic function of H and its gradients. The free energy