Develop

LICENSE

@@ -1,40 +1,201 @@
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-2. Redistribution of source or binary forms of the software includes the copyright notice, this list of conditions, and the disclaimer.
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README.md

@@ -16,12 +16,21 @@ Status: ![Workflow name](https://github.com/JoshuaAlbert/jaxns/actions/workflows
 
 JAXNS is:
 
-1) a probabilistic programming framework using nested sampling as the engine;
+1) a simple and powerful probabilistic programming framework using nested sampling as the engine;
 2) coded in JAX in a manner that allows lowering the entire inference algorithm to XLA primitives, which are
    JIT-compiled for high performance;
 3) continuously improving on its mission of making nested sampling faster, easier, and more powerful; and
 4) citable, use the [(old) pre-print here](https://arxiv.org/abs/2012.15286).
 
+What can you do with JAXNS?
+
+1) Compute the Bayesian evidence of a model or hypothesis (the ultimate scientific method); 
+2) Produce high-quality samples from the posterior distribution;
+3) Easily handle degenerate difficult multi-modal posteriors;
+4) Model both discrete and continuous priors and likelihoods;
+5) Encode complex constraints on the prior space;
+6) Easily embed neural networks or any other ML model in the likelihood/prior;
+
 ## JAXNS Probabilistic Programming Framework
 
 JAXNS provides a powerful JAX-based probabilistic programming framework, which allows you to define probabilistic
@@ -239,7 +248,7 @@ from jaxns.experimental import EvidenceMaximisation
 
 # Let's train the sigma parameter to maximise the evidence
 
-em = EvidenceMaximisation(model, ns_kwargs=dict(max_samples=1e4))
+em = EvidenceMaximisation(model)
 results, params = em.train(num_steps=5)
 
 summary(results, with_parametrised=True)
@@ -350,6 +359,10 @@ before importing JAXNS.
 
 # Change Log
 
+4 Nov, 2024 -- JAXNS 2.6.4 released. Resolved bias when using phantom points.
+
+1 Oct, 2024 -- JAXNS 2.6.3 released. Enable pytrees in context.
+
 25 Sep, 2024 -- JAXNS 2.6.2 released. Fixed some important (not so edge) cases. Made faster. Handle no seed scenarios.
 
 24 Sep, 2024 -- JAXNS 2.6.1 released. Sharded parallel JAXNS. Rewrite of internals to support sharded parallelisation.