AITowards Data Scienceabout 10 hours ago
Cosmologist Switches to Diffrax for Faster Bayesian Inference
1 min read
A theoretical cosmologist switched from SciPy's ODE solvers to JAX-powered Diffrax, achieving faster likelihood evaluations and scalable Bayesian inference. The ODE solve alone took 0.4 ms per call, costing 40 seconds in a nested sampling run. Gradients via finite differences added 5 minutes. Diffrax provides exact automatic differentiation and improved performance for complex cosmological models.
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