<h2>Overview</h2>
<p>MCX is a probabilistic programming library focused on sampling methods. It transforms model definitions to generate logpdf or sampling functions, JIT-compiled with JAX, supporting batching on CPU, GPU, or TPU. It aims to offer sequential inference and performant sampling methods for Bayesian deep learning.</p>
<h2>Features</h2>
<ul>
<li>Laser-focus on sampling methods</li>
<li>JIT-compiled with JAX for GPU and TPU support</li>
<li>Modular and re-usable model definitions</li>
<li>Batch sampling runtime with interactive mode for real-time monitoring</li>
<li>Support for neural network layers, stochastic support, and causal inference tools</li>
</ul>


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