Parallel Dirichlet Process Slice Sampler
Dirichlet Process is a promising prior for learning non-parametric mixture models. It determines the number of parameters used in the model according to data. In this implementation slice sampler is used to have parallelization. The code is implemented in C++ with avoiding unnecessary memory allocations. Wrapper functions in Matlab and Python allow processing input/output easier.
Check details of the slice sampler : http://www.jmlr.org/proceedings/papers/v37/gea15.pdf
Cite As
Halid Ziya Yerebakan (2025). Parallel Dirichlet Process Slice Sampler (https://github.com/halidziya/DPSlice), GitHub. Retrieved .
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Versions that use the GitHub default branch cannot be downloaded
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| 1.1.0.0 | More representative image
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| 1.0.0.0 | Parallel Update on description
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