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Releases: bb515/diffusionjax

Bring release up to latest stable version

19 Jan 15:33
24fb2c8

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Merge pull request #34 from bb515/develop

Develop

Make explicit the equivalence between discrete markov chains and continuous time numerical solvers

23 Jan 10:32
aeb5de9

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Rerelease of 0.1.6 old that had a bug in VE Markov chains. This changes the api a bit, especially for SDEs, but things are more general and explicit and you can now use a cosine beta schedule (or any beta schedule) too.

0.1.5

31 Oct 15:27
7c19a68

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The "Bayes update". Added new inverse guidance methods, approximately sample from approximate(p(x|y)) given diffusion model p(x) and data y.

0.1.4

26 Oct 11:07
d0d5d30

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Refactor sde class to be more pythonic (flat).
Added bayesian inversion methods for linear inverse problems.
Added linting, refactored, then removed again since linting was not compatible with python 3.7 or 3.8.

0.1.3

20 Oct 14:47
3d7c52b

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Change sde class structure and add flake8, ruff and mypy

0.1.2

10 Oct 15:57
3b97ea5

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New linting, remove requirements.txt in favour of extras in setup.py, improve CI workflow, change linting so that tab is 2 spaces rather than 4, refactor so that no longer directly depend on orbax or optax, and make clear those dependencies that only occur within the examples.

0.1.1

18 Sep 23:25
d2efa0d

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Markov chains!

0.1.0

22 Aug 14:29
5792b7f

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Update to 0.1.0. This update includes

  • a planned deprecation of meth:utils.update_step
  • jit multiple training steps together
  • full support for pmap across devices (GPU/TPU) of the same model
  • refactoring to make library simpler, flatter
  • bug fixes and minor improvements

0.0.9

11 May 08:53
f0c7df5

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Made pmap optional