RxInfer is specifically designed for real-time Bayesian inference, which sets it apart from many other approaches. You can’t reliably compare it to “competing Bayesian inference methods” because most of them rely on sampling, which is simply too computationally expensive to be used in real-time. While RxInfer may introduce some approximation error, sampling-based methods are often too slow to produce any result within the required time frame.

For example, in our portfolio we have a comparison with NumPyro on Bayesian linear regression: https://examples.rxinfer.com/categories/basic_examples/bayes.... While this isn’t a real-time signal processing use case, it still shows that RxInfer can match the quality of NumPyro’s results—at a fraction of the computational cost