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## Uses of Package
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

Packages that use de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
de.jstacs.sequenceScores.statisticalModels.differentiable | Provides all `DifferentiableStatisticalModel`s, which can compute the gradient with respect to their parameters for a given input `Sequence`.
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous | Provides `DifferentiableStatisticalModel`s that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif |

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous used by de.jstacs.sequenceScores.statisticalModels.differentiable
HomogeneousDiffSM This is the main class for all homogeneous `DifferentiableSequenceScore`s.
HomogeneousMMDiffSM This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous used by de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
HomogeneousDiffSM This is the main class for all homogeneous `DifferentiableSequenceScore`s.
HomogeneousMM0DiffSM This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
HomogeneousMMDiffSM This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous used by de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif
HomogeneousDiffSM This is the main class for all homogeneous `DifferentiableSequenceScore`s.

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