代码搜索:Inference

找到约 1,820 项符合「Inference」的源代码

代码结果 1,820
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m cond_gauss_inf_engine.m

function engine = cond_gauss_inf_engine(bnet) % COND_GAUSS_INF_ENGINE Conditional Gaussian inference engine % engine = cond_gauss_inf_engine(bnet) % % Enumerates all the discrete roots, and runs jtree
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m belprop_fg_inf_engine.m

function engine = belprop_fg_inf_engine(fg, varargin) % BELPROP_FG_INF_ENGINE Make a belief propagation inference engine for factor graphs % engine = belprop_fg_inf_engine(factor_graph, ...) % % The
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m hmm_inf_engine.m

function engine = hmm_inf_engine(bnet, varargin) % HMM_INF_ENGINE Inference engine for DBNs which uses the forwards-backwards algorithm. % engine = hmm_inf_engine(bnet, ...) % % The following optional
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m jtree_dbn_inf_engine.m

function engine = jtree_dbn_inf_engine(bnet, varargin) % JTREE_DBN_INF_ENGINE Junction tree inference algorithm for DBNs. % engine = jtree_inf_engine(bnet, ...) % % The following optional arguments ca
www.eeworm.com/read/343323/3221072

java tuple.java

//: net/mindview/util/Tuple.java // Tuple library using type argument inference. package net.mindview.util; public class Tuple { public static TwoTuple tuple(A a, B b) { return
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java tuple.java

//: net/mindview/util/Tuple.java // Tuple library using type argument inference. package net.mindview.util; public class Tuple { public static TwoTuple tuple(A a, B b) { return
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java tuple.java

//: net/mindview/util/Tuple.java // Tuple library using type argument inference. package net.mindview.util; public class Tuple { public static TwoTuple tuple(A a, B b) { return
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scala s1.scala

/* This is probably no bug, I just don't understand why ** type inference does not find the right instantiation of foo. ** Currently it reports: ** ** S1.scala:12: inferred type arguments [S1] do not
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java tuple.java

//: net/mindview/util/Tuple.java // Tuple library using type argument inference. package net.mindview.util; public class Tuple { public static TwoTuple tuple(A a, B b) { return
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m scg3.m

% Compare various inference engines on the following network (from Jensen (1996) p84 fig 4.17) % 1 % / | \ % 2 3 4 % | | | % 5 6 7 % \/ \/ % 8 9 % where all arcs point downwards N = 9;