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The article presents SenseTime's PPL framework, detailing its toolchain, inference engine, multi‑backend operator library, quantization tools, CUDA optimizations, performance benchmarks across CPUs, GPUs, DSPs and DSAs, and outlines future plans for broader chip support and AI for Science.
This article explains the principles of probabilistic programming languages and walks through a step‑by‑step implementation of a minimal PPL in Python, covering model definition, variable representation, DAG traversal, log‑density computation, and a posterior grid illustration.
This article explains the principles of probabilistic programming languages and walks through constructing a basic PPL in Python, covering model definition with latent and observed variables, distribution handling, DAG traversal for log‑density computation, and demonstrates evaluation with example code and visualizations.
This article explains how probabilistic programming languages work and walks through building a minimal PPL in Python, covering model definition, latent and observed variables, DAG traversal, log‑density computation, and extensions such as posterior grid approximation.