Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. PHP, C++, .NET, Ada, Python, Delphi, Octave, Ruby, Prolog Pure Data and Mathematica bindings are available. A reference manual accompanies the library with examples and recommendations on how to use the library. A graphical user interface is also available for the library.
H. Li, Z. Xu, G. Taylor, C. Studer, and T. Goldstein. (2017)cite arxiv:1712.09913Comment: NIPS 2018 (extended version, 10.5 pages), code is available at https://github.com/tomgoldstein/loss-landscape.
S. Merity. (2019)cite arxiv:1911.11423Comment: Addition of citations and contextual results (no attention head, single attention head, attention per layer), removal of wordpiece WikiText-103 numbers due to normalization issues, fix of SHA attention figure Q arrow, other minor fixes.