Abstract: A data calculation device including a high-level posterior distribution data calculator for calculating data indicating a posterior distribution of parameter values of a high-level model that simulates a subject, based on target data for outputs from the high-level model; and a low-level posterior distribution data calculator for calculating, for a low-level model that simulates a portion of the subject and that outputs parameter values of the high-level model, data indicating a posterior distribution of parameter values of the low-level model, based on the data indicating a posterior distribution of parameter values of the high-level model.

Abstract: A model generation device includes: a model generation means for generating a second model indicating a relationship between a parameter included in a first model and a sample, the first model indicating a relationship between the sample and a label of the sample.

Abstract: A model generation device includes a model generation unit that generates a third model indicating a relationship between a first model and a parameter of a second model, the first model indicating a relationship between a sample and a label of the sample, the second model indicating the relationship and being different from the first model.

Abstract: A search device includes: a relationship calculation means for calculating a relationship by using a plurality of sets, each set including a parameter value and a numerical value indicating a degree of occurrence of a target event in a case of the parameter value, the relationship being a relationship between the parameter value and the numerical value; a frequency calculation means for calculating, for a plurality of bins obtained by dividing up a range that can be taken by the numerical value, a frequency at which the numerical value is included in a bin; a number setting means for performing, for at least some bins of the plurality of bins, a setting relating to a number of the parameter value such that the lower the frequency of the bin, the greater a number of the parameter value serving as calculation subjects of the numerical value, by using the frequency; and a parameter setting means for setting parameter values by the set number.

Abstract: An information processing apparatus includes: a corresponding data calculation unit configured to determine importance of each sample in accordance with a difference between a plurality of pieces of observation information observed when an input is given to an observation target and data of a second type generated by a simulator that simulates the observation target based on a sample of a parameter with respect to a plurality of samples and data of a first type indicating the input, and a degree of influence of the sample on distribution of parameters, and then calculate data that corresponds to the distribution of the parameters; a new parameter sample generation unit configured to generate a new sample of the parameters in accordance with predetermined processing using the data that corresponds to the distribution of the parameters; and an iteration control unit configured to perform control so as to repeat the above processing.

Abstract: An analysis device applies, for each of a plurality of candidates set according to a update target parameter value, the update target parameter value and the candidate to a machine learning result to acquire information, the information indicating a degree of difference of an evaluation target value in a case of the candidate with respect to an evaluation target value in a case of the update target parameter value; calculates, for each candidate, an evaluation target value in a case of the candidate, based on the degree of difference of the evaluation target values and the evaluation target value in the case of the update target parameter value; and compares the evaluation target values in a case of each of the plurality of candidates and selects a candidate from the plurality of candidates based on a result of the comparison.

Abstract: Parameters are efficiently calculated. An information processing apparatus (1) includes a corresponding data calculation unit (2) configured to determine importance of each sample in accordance with a difference between a plurality of pieces of observation information observed when an input is given to an observation target and data of a second type generated by a simulator that simulates the observation target based on a sample of a parameter with respect to the plurality of samples and data of a first type indicating the input, and a contribution degree of each of the pieces of observation information in the plurality of pieces of observation information, and calculate data that corresponds to distribution of the parameters; and a new parameter sample generation unit (3) configured to generate a new sample of the parameters in accordance with predetermined processing using data that corresponds to distribution of the parameters.

Abstract: An analysis device applies, for each of a plurality of candidates for an updated parameter value set according to an update target parameter value, the update target parameter value and the candidate to a plurality of machine learning results to acquire, for each machine learning result, information indicating a degree of difference of an evaluation target value in a case of the candidate with respect to an evaluation target value in a case of the update target parameter value; calculate, for each candidate and for each machine learning result, an evaluation target value in the case of the candidate based on the degree of difference and the evaluation target value in the case of the update target parameter value; and calculate a selection index value for each candidate using a variation in the evaluation target values for each machine learning result, compare the selection index value of each candidate.

Abstract: An analysis device includes a parameter sample data calculation unit that calculates a plurality of pieces of sample data for parameters for a simulator, based on a temporarily set distribution for the parameters, the simulator receiving inputs of data of a first type and outputting data of a second type; a second type sample data acquisition unit that inputs, to the simulator, target data of the first type indicating a target value for the data of the first type and sample data for the parameters and obtains sample data of the second type for each of the plurality of pieces of sample data for the parameters; and a parameter value calculation unit that calculates a weight for each of the plurality of pieces of sample data for the parameters based on the difference between target data of the second type indicating a target value for the data of the second type and the calculated sample data of the second type and based on the relationship between a first distribution followed by the target data of the first ty

Abstract: An analysis device includes a parameter sample data calculation unit that calculates a plurality of pieces of sample data for parameters for a simulator; a second type sample data acquisition unit that inputs, to the simulator, target data of the first type and each of the plurality of pieces of sample data for the parameters and obtains sample data of the second type for each of the plurality of pieces of sample data; and a parameter value calculation unit that calculates a weight for each of the plurality of pieces of sample data based on the difference between target data of the second type and the calculated sample data of the second type and calculates, using the calculated weight, a value for the parameters corresponding to the target data of the first type and the target data of the second type.

Abstract: A relationship analysis device includes a parameter sample data calculation unit that calculates sample data for parameters for a simulator that receives inputs of data of a first type and outputs data of a second type, calculating sample data; a second type sample data acquisition unit that inputs, to the simulator, observation data and sample data, and obtains sample data of the second type; and a parameter value determination unit that calculates a weight for sample data based on the difference between observation data of the second type and the sample data of the second type, and based on the relationship between a first distribution that the observation data of the first type followed and a second distribution being a distribution of the data of the first type, and calculates a value for the parameters using the calculated weight.

Abstract: A relationship analysis device includes a parameter sample data calculation unit that calculates a plurality of pieces of sample data for parameters for a simulator that receives inputs of data of a first type and outputs data of a second type, calculating the plurality of pieces of sample data; a second type sample data acquisition unit that inputs, to the simulator, observation data of the first type and a plurality of pieces of sample data, and obtains sample data of the second type for each of the plurality of pieces of sample data; and a parameter value determination unit that calculates a weight for each of the plurality of pieces of sample data based on the difference between observation data of the second type and the calculated sample data of the second type and calculates a value for the parameters using the calculated weight.