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Update README.md #37

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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -11,7 +11,7 @@ Baylib is a parallel inference library for discrete Bayesian networks supporting
## Main features
Here's a list of the main requested features:
* Copy-On-Write semantics for the graph data structure, including the conditional probability table (CPT) of each node
* parallel implementation of the algorithms either using C++17 threads or GPGPUU optimization
* parallel implementation of the algorithms either using C++17 threads or GPGPU optimization
* GPGPU optimization implemented with opencl, using [boost compute](https://www.boost.org/doc/libs/1_66_0/libs/compute/doc/html/index.html) and CUDA.
* template-based classes for probability format
* input compatibility with the [XDSL format](https://support.bayesfusion.com/docs/) provided by the SMILE library
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