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template<typename T , typename Scalar > |
double | bnmf_algs::alloc_model::log_marginal_S (const tensor_t< T, 3 > &S, const Params< Scalar > &model_params) |
| Compute the log marginal of tensor S with respect to the given distribution parameters. More...
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template<typename T , typename Scalar > |
double | bnmf_algs::details::compute_first_term (const tensor_t< T, 3 > &S, const std::vector< Scalar > &alpha) |
| Compute the first term of the sum when calculating log marginal of S. More...
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template<typename T , typename Scalar > |
double | bnmf_algs::details::compute_second_term (const tensor_t< T, 3 > &S, const std::vector< Scalar > &beta) |
| Compute the second term of the sum when calculating log marginal of S. More...
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template<typename T , typename Scalar > |
double | bnmf_algs::details::compute_third_term (const tensor_t< T, 3 > &S, Scalar a, Scalar b) |
| Compute the third term of the sum when calculating log marginal of S. More...
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template<typename T > |
double | bnmf_algs::details::compute_fourth_term (const tensor_t< T, 3 > &S) |
| Compute the fourth term of the sum when calculating log marginal of S. More...
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template<typename T , typename Scalar > |
std::tuple< matrix_t< T >, matrix_t< T >, vector_t< T > > | bnmf_algs::alloc_model::bnmf_priors (const shape< 3 > &tensor_shape, const Params< Scalar > &model_params) |
| Return prior matrices W, H and vector L according to the Bayesian NMF allocation model using distribution parameters. More...
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template<typename T > |
tensor_t< T, 3 > | bnmf_algs::alloc_model::sample_S (const matrix_t< T > &prior_W, const matrix_t< T > &prior_H, const vector_t< T > &prior_L) |
| Sample a tensor S from generative Bayesian NMF model using the given priors. More...
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template<typename Integer , typename Scalar > |
double | bnmf_algs::alloc_model::total_log_marginal (const matrix_t< Integer > &X, const Params< Scalar > &model_params) |
| Calculate total marginal value, \(p(X|\Theta) = \sum_S p(X|S)p(S|\Theta)\) where \(Theta\) is model parameters. More...
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