Probabilistic Modeling
Showing 6 of 6 projects
A flexible, scalable deep probabilistic programming library built on PyTorch for universal representation of computable probability distributions.
A flexible, scalable deep probabilistic programming library built on PyTorch for universal probabilistic modeling.
A highly efficient, scalable Gaussian process library implemented in PyTorch with GPU acceleration and modular design.
A Python library for probabilistic modeling built on PyTorch, offering modular distributions, GPU support, and flexible model composition.
An open-source Python library for probabilistic time series modeling with both frequentist and Bayesian inference methods.
A Python library for deep probabilistic modeling and analysis of single-cell and spatial omics data.
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