Markov Chain
سلسلة ماركوف الاحتمالية
نموذج احتمالي يعتمد على فرضية أن احتمال الانتقال للحالة المستقبلية يعتمد حصراً على الحالة الراهنة.
Markov Chain
Also translated asمتتالية الحالات عديمة الذاكرة، التتابع الاحتمالي المرتبط بالحالة الحالية
First appears in this corpus in: Extension of the Law of Large Numbers to Dependent Quantities (1906)
Appears in these papers
- Practical Bayesian Optimization of Machine Learning Algorithms2012in the sky ✦
- Denoising Diffusion Implicit Models2021in the sky ✦
- Denoising Diffusion Implicit Models2021in the sky ✦
- Denoising Diffusion Probabilistic Models2020in the sky ✦
- Denoising Diffusion Probabilistic Models2020in the sky ✦
- Deep Speech 2: End-to-End Speech Recognition in English and Mandarin2015in the sky ✦
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images1984in the sky ✦
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images1984in the sky ✦
- A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition1989in the sky ✦
- A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition1989in the sky ✦
- A New Approach to Linear Filtering and Prediction Problems1960in the sky ✦
- Extension of the Law of Large Numbers to Dependent Quantities1906in the sky ✦
- Extension of the Law of Large Numbers to Dependent Quantities1906in the sky ✦
- Equation of State Calculations by Fast Computing Machines1953in the sky ✦
- Equation of State Calculations by Fast Computing Machines1953in the sky ✦
- The Monte Carlo Method1949in the sky ✦
- Optimization by Simulated Annealing1983in the sky ✦
- Learning to Predict by the Methods of Temporal Differences1988in the sky ✦
- Auto-Encoding Variational Bayes2013in the sky ✦