English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Interpretable embeddings from molecular simulations using Gaussian mixture variational autoencoders

MPS-Authors
/persons/resource/persons260234

Bozkurt Varolgunes,  Yasemin
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;
Koc Univ, Dept Elect & Elect Engn, Istanbul, Turkey;

/persons/resource/persons130617

Bereau,  Tristan
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

/persons/resource/persons185417

Rudzinski,  Joseph F.
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
Supplementary Material (public)
There is no public supplementary material available
Citation

Bozkurt Varolgunes, Y., Bereau, T., & Rudzinski, J. F. (2020). Interpretable embeddings from molecular simulations using Gaussian mixture variational autoencoders. Machine Learning: Science and Technology, 1(1): 015012. doi:10.1088/2632-2153/ab80b7.


Cite as: https://hdl.handle.net/21.11116/0000-0009-69D7-F
Abstract
There is no abstract available