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[PRE REVIEW]: PolytopeWalk: Sparse MCMC Sampling over Polytopes #7872
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Five most similar historical JOSS papers: pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology Efficient Polyhedral Gravity Modeling in Modern C++ and Python MParT: Monotone Parameterization Toolkit pyOptSparse: A Python framework for large-scale constrained nonlinear optimization of sparse systems sparse-lm: Sparse linear regression models in Python |
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👋 @bsun1220 - while I am getting a topic editor assigned to your submission, please reduce the word count of your paper to <= 1000 words. Thanks. |
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Five most similar historical JOSS papers: Efficient Polyhedral Gravity Modeling in Modern C++ and Python PxMCMC: A Python package for proximal Markov Chain Monte Carlo MParT: Monotone Parameterization Toolkit pyOptSparse: A Python framework for large-scale constrained nonlinear optimization of sparse systems PyVBMC: Efficient Bayesian inference in Python |
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Using the reviewer suggestions from matt-graham who has a different paper on MCMC algorithms, @vissarion if you need help finding reviewers, I saw that larryshamalama, vankesteren, robmoss, njtierney and martinmodrak all had relevant profiles. |
Submitting author: @bsun1220 (Benny Sun)
Repository: https://github.com/ethz-randomwalk/polytopewalk
Branch with paper.md (empty if default branch):
Version: v1.0.17
Editor: @vissarion
Reviewers: Pending
Managing EiC: Chris Vernon
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