Markov Chain Mixture Models for Real‐Time Direct Illumination

Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models

The Pitman-Yor process provides an elegant way to cluster data that exhibit power law behavior, where the number of clusters is unknown or unbounded. Unfortunately, inference in PitmanYor process-based models is typically slow and does not scale well with dataset size. In this paper we present new auxiliary-variable representations for the Pitman-Yor process and a special case of the hierarchic...

Markov Chain Sampling Methods for Dirichlet Process Mixture Models

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Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models

Nonparametric mixture models based on the Dirichlet process are an elegant alternative to finite models when the number of underlying components is unknown, but inference in such models can be slow. Existing attempts to parallelize inference in such models have relied on introducing approximations, which can lead to inaccuracies in the posterior estimate. In this paper, we describe auxiliary va...

analysis of ruin probability for insurance companies using markov chain

در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...

Markov Chain Monte Carlo Methods for Global Illumination