The version release focuses on cleaning up the internal API, which should makes the study of auto-tuning way easier now. The top level API remains relatively unchanged. On the performance side, most noticeably the compilation time of the normalizing flow has been reduced significantly.
For the next version of flowMC (0.4.0), the main focus will be some sort of auto-tune and adding more potential strategies in the mix, including 1. using importance sampling with normalizing flow to further improve the sampling results 2. Start the normalizing flow with some variational inference scheme instead of from scratch.
What's Changed
* Bayeux example by kazewong in https://github.com/kazewong/flowMC/pull/146
* Added plotting utilities and refactored hyperparams by ThibeauWouters in https://github.com/kazewong/flowMC/pull/143
* small bug fix in keys for stepping optimizer by tedwards2412 in https://github.com/kazewong/flowMC/pull/148
* Sync branch 134 by kazewong in https://github.com/kazewong/flowMC/pull/150
* 134 add precommit script and fix formatting by kazewong in https://github.com/kazewong/flowMC/pull/151
* 144 get rid of random key set by kazewong in https://github.com/kazewong/flowMC/pull/152
* 153 use scan to reduce nf compilation time by kazewong in https://github.com/kazewong/flowMC/pull/154
* Sync branch 142 by kazewong in https://github.com/kazewong/flowMC/pull/155
* 142 sampling from arrays by kazewong in https://github.com/kazewong/flowMC/pull/156
* Update README.md by kazewong in https://github.com/kazewong/flowMC/pull/159
* 158 put training loop into nf class by kazewong in https://github.com/kazewong/flowMC/pull/160
* 157 making sampler composable by kazewong in https://github.com/kazewong/flowMC/pull/161
New Contributors
* ThibeauWouters made their first contribution in https://github.com/kazewong/flowMC/pull/143
* tedwards2412 made their first contribution in https://github.com/kazewong/flowMC/pull/148
**Full Changelog**: https://github.com/kazewong/flowMC/compare/flowMC-0.2.4...flowMC-0.3.0