What's new

This version brings lots of new functionalities, improvements and fixes many small bugs and issues. We have a new theme for the TensorLy project's documentations, our new TensorLy Sphinx theme, which we've open-sourced and that you can also easily use in your own projects! We've also switched testing from Travis to Github actions and for coverage, from Coveralls to CodeCov.

New features

• Non-negative CP decomposition via Hierarchical Alternating Least Square (HALS), thanks to @caglayantuna and @cohenjer, [#224]
• Non-negative SVD and refactoring of non-negative CP, thanks to @aarmey, [#204]
• Randomized SVD thanks to @merajhashemi, [#215]
• Sign correction method for CP thanks to @aarmey, [#226]
• Support for complex tensors, thanks to @merajhashemi [#213], [#247]
• Entropy metrics, thanks to @taylorpatti, [#231]

Backend refactoring

• Various SVD forms are backend-agnostic.
• Norm method is backend-agnostic.
• CuPy tests now pass thanks to @aarmey, [#217]
• Random number generation seed (check_random_state) was moved to the backend, and random functions now use NumPy’s global seed by default thanks to @merajhashemi, [#209] [#212]
• Using mxnet.np interface in MXNet backend, thanks to @aarmey, [#225], [#207]

Bug fixes and improvements

• PARAFAC2: fixed SVD init and improved naming consistency, thanks to @MarieRoald, [#220]
• Improved CP initialisation thanks to @caglayantuna, [#230]
• Improved testing for check_tucker_rank
• Support for order-1 and 2 CP and TT/TTM tensors.
• Fixed issues in CP via robust tensor power iteration, thanks to @chrisyeh96, [#244]
• Added support for tensordot in all backends
• Fix for partial_tucker when provided with mask and applied only to a subset of modes, [691f78]
• Documentation and user-guide improvements, switched to new theme, [e328d8]

And many other small improvements!