推論技術:inference Technology

Protected: Drones and 3D Model Reconstruction Technology

Drones and 3D model recovery technology (SfM, MVS) used for geographic information processing for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks

2022.08.02

IOT技術:IOT TechnologyStream Data Processingアルゴリズム:Algorithms地理空間情報処理推論技術:inference Technology機械学習:Machine Learning画像認識技術

Genetic Programming Theory and Practice X Papers

Artificial Intelligence Technology Semantic Web Technology Knowledge Information Processing Technology Reasoning Tech...

2022.07.31

LISPアルゴリズム:Algorithms推論技術:inference Technology深層学習:Deep Learning

KI 2016: Advances in Artificial Intelligence Papers

KI2016 In the previous article, I described KI 2015. In this article, we describe the 39th Ger...

2022.07.30

セマンテックウェブ技術:Semantic web Technology推論技術:inference Technology

Protected: Computing Peripheral Probability Distributions – Mean Field Approximation

Application of graphical models to stochastic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks; approximate computation and algorithms for peripheral probability distributions from variational problems using mean field approximation

2022.07.28

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Variational Bayesian Learning Framework and Algorithms

Overview of variational Bayesian learning and algorithms (variational Bayesian learning, empirical variational Bayesian learning) for approximate computation of complex models in stochastic generative models used in digital transformation, artificial intelligence, and machine learning tasks.

2022.07.27

アルゴリズム:Algorithms推論技術:inference Technology機械学習:Machine Learning確率・統計:Probability and Statistics

Protected: Comparison of clustering using k-means and Bayesian estimation methods (mixed Gaussian model)

Comparison of k-means and Bayesian estimation (mixed Gaussian model) clustering as probabilistic generative models utilized in digital transformation, artificial intelligence , and machine learning tasks

2022.07.26

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Overview of Gaussian Processes(5)Generalization of Gaussian Process Regression

Extensions of probabilistic generative models utilized in digital transformation, artificial intelligence, and machine learning tasks and generalizations of the Cauchy distribution of Gaussian processes as robustness collateral, Gaussian process identification models, and Poisson distributions for machine failure, elementary particle decay, etc.

2022.07.25

アルゴリズム:Algorithmsベイズ推定微分積分:Calculus推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

KI 2015: Advances in Artificial Intelligence Papers

KI 2015: Advances in Artificial Intelligence In the previous article, I described KI 2014. In this i...

2022.07.23

コンピューターセマンテックウェブ技術:Semantic web Technology推論技術:inference Technology

Protected: Calculation of marginal probability distribution – Kikuchi approximation

Application of graphical models to stochastic generative models for digital transformation, artificial intelligence, and machine learning tasks; calculation of marginal probability distributions in the generalized stochastic propagation method with Kikuchi free energy functions and comparison with Bethe free energy functions and Hasse diagrams

2022.07.21

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra

Protected: Overview of Bayesian Estimation with Concrete Examples

Calculate the fundamentals of Bayesian estimation (exchangeability, de Finetti's theorem, conjugate prior distribution, posterior distribution, marginal likelihood, etc.) used in probabilistic generative models for digital transformation, artificial intelligence, and machine learning tasks, based on concrete examples (Dirichlet-multinomial distribution model, gamma-gaussian distribution model).

2022.07.20

アルゴリズム:Algorithmsグラフ理論ベイズ推定微分積分:Calculus推論技術:inference Technology最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics線形代数:Linear Algebra