DynetSharp (nuget): DyNet is a neural network library developed by Carnegie Mellon University and many others. It is written in C++ (with bindings in Python and C#) and is designed to be efficient when run on either CPU or GPU, and to work well with networks that have dynamic structures that change for every training instance. For example, these kinds of networks are particularly important in natural language processing tasks, and DyNet has been used to build state-of-the-art systems for syntactic parsing (https://github.com/clab/lstm-parser), machine translation (https://github.com/neubig/lamtram), morphological inflection (https://github.com/mfaruqui/morph-trans), and many other application areas.  Read the documentation (http://dynet.readthedocs.io/en/latest/) to get started, and feel free to contact the dynet-users group (https://groups.google.com/forum/#!forum/dynet-users) group with any questions (if you want to receive email make sure to select "all email" when you sign up). We greatly appreciate any bug reports and contributions, which can be made by filing an issue or making a pull request through the github page (http://github.com/clab/dynet).  You can also read more technical details in our technical report (https://arxiv.org/abs/1701.03980).
Keywords: machine|learning|dynet|neural|networks|dynamic|lstm|rnn|lm|language|model|mlp