代码搜索:Inference
找到约 1,820 项符合「Inference」的源代码
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www.eeworm.com/read/420035/2072947
java new.java
//: net/mindview/util/New.java
// Utilities to simplify generic container creation
// by using type argument inference.
package net.mindview.util;
import java.util.*;
public class New {
publ
www.eeworm.com/read/397335/2403451
java new.java
//: net/mindview/util/New.java
// Utilities to simplify generic container creation
// by using type argument inference.
package net.mindview.util;
import java.util.*;
public class New {
publ
www.eeworm.com/read/396844/2407277
m belprop_inf_engine.m
function engine = belprop_inf_engine(bnet, varargin)
% BELPROP_INF_ENGINE Make a loopy belief propagation inference engine
% engine = belprop_inf_engine(bnet, ...)
%
% This is like pearl_inf_engine,
www.eeworm.com/read/396844/2407313
m var_elim_inf_engine.m
function engine = var_elim_inf_engine(bnet, varargin)
% VAR_ELIM_INF_ENGINE Variable elimination inference engine
% engine = var_elim_inf_engine(bnet)
%
% For details on variable elimination, see
% -
www.eeworm.com/read/396844/2407316
readme
% Stable conditional Gaussian inference
% Written by Huang, Shan
% Copyright (c) Intel Corporation 2001
% See
@techreport{Lauritzen99,
author = "S. Lauritzen and F. Jensen",
www.eeworm.com/read/396844/2407349
m ff_inf_engine.m
function engine = ff_inf_engine(bnet)
% FF_INF_ENGINE Factored frontier inference engine for DBNs
% engine = ff_inf_engine(bnet)
%
% The model must be topologically isomorphic to an HMM.
% In addition
www.eeworm.com/read/396844/2407425
m frontier_inf_engine.m
function engine = frontier_inf_engine(bnet)
% FRONTIER_INF_ENGINE Inference engine for DBNs which which uses the frontier algorithm.
% engine = frontier_inf_engine(bnet)
%
% The frontier algorithm ext
www.eeworm.com/read/396844/2407530
readme
% Stable conditional Gaussian inference
% Written by Huang, Shan
% Copyright (c) Intel Corporation 2001
% See
@techreport{Lauritzen99,
author = "S. Lauritzen and F. Jensen",
www.eeworm.com/read/393163/2487881
m chmm1.m
% Compare the speeds of various inference engines on a coupled HMM
N = 3;
Q = 2;
rand('state', 0);
randn('state', 0);
discrete = 0;
if discrete
Y = 2; % size of output alphabet
else
Y = 3; % size
www.eeworm.com/read/393163/2487887
m kjaerulff1.m
% Compare the speeds of various inference engines on the DBN in Kjaerulff
% "dHugin: A computational system for dynamic time-sliced {B}ayesian networks",
% Intl. J. Forecasting 11:89-111, 1995.
%
% Th