arXiv:2404.04738
공식 코드 · Papers with Code
BARMPy: Bayesian Additive Regression Models Python Package
원문 초록
We make Bayesian Additive Regression Networks (BARN) available as a Python package, \texttt{barmpy}, with documentation at \url{https://dvbuntu.github.io/barmpy/} for general machine learning practitioners. Our object-oriented design is compatible with SciKit-Learn, allowing usage of their tools like cross-validation. To ease learning to use \texttt{barmpy}, we produce a companion tutorial that expands on reference information in the documentation. Any interested user can \texttt{pip install barmpy} from the official PyPi repository. \texttt{barmpy} also serves as a baseline Python library for generic Bayesian Additive Regression Models.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Near-Polynomially Competitive Active Logistic Regression
Active Learning for Manifold Gaussian Process Regression
Vector Contrastive Learning For Pixel-Wise Pretraining In Medical Vision
GRASP: Grouped Regression with Adaptive Shrinkage Priors
CAWR: Corruption-Averse Advantage-Weighted Regression for Robust Policy Optimization
Scaling-Up the Pretraining of the Earth Observation Foundation Model PhilEO to the MajorTOM Dataset
토론
이 논문과 연결된 포럼 글이 아직 없습니다.