1.3.5

• Added automatic posterior approximations in variational inference (#775).
• Added use of tf.GraphKeys.REGULARIZATION_LOSSES to variational inference (#813).
• Added multinomial classification metrics (#743).
• Added utility function to assess conditional independence (#791).
• Added custom metrics in evaluate.py (#809).
• Minor bug fixes, including automatic transformations (#808); ratio inside ed.MetropolisHastings (#806).

Acknowledgements

• Thanks go to Baris Kayalibay (@bkayalibay), Christopher Lovell (@christopherlovell), David Moore (@davmre), Kris Sankaran (@krisrs1128), Manuel Haussmann (@manuelhaussmann), Matt Hoffman (@matthewdhoffman), Siddharth Agrawal (@siddharth-agrawal), William Wolf (@cavaunpeu), @gfeldman.

We are also grateful to all who filed issues or helped resolve them, asked and answered questions, and were part of inspiring discussions.