Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
COBOSLAB: Cognitive Bodyspaces: Learning and Behavior:
Laboratory that investigates and models the Self-organized Learning of and Behavior within Integrated Multimodal Multimodular Bodyspace Representations.
Neuroph is lightweight Java neural network framework to develop common neural network architectures. It contains well designed, open source Java library with small number of basic classes which correspond to basic NN concepts. Also has nice GUI neural network editor to quickly create Java neural network components. It has been released as open source under the LGPL license, and it's FREE for you to use it.
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
SIMBRAIN is a free tool for building, running, and analyzing neural-networks (computer simulations of brain circuitry). Simbrain aims to be as visual and easy-to-use as possible.
JavaNNS is the successor of SNNS. It is based on its computing kernel, with a newly developed, comfortable graphical user interface written in Java set on top of it. Hence the compatibility with SNNS is achieved, while the platform-independence is increa
If you are starting with Neural Networks you should check out my online book on the subject. It contains over 300 pages of information on Neural Network Programming in Java. You can access it here.
Get the entire book! Introduction to Neural Networks with Java Programming Neural Networks in Java will show the intermediate to advanced Java programmer how to create neural networks. This book attempts to teach neural network programming through two mec
J. Weyn, D. Durran, and R. Caruana. Journal of Advances in Modeling Earth Systems, 11 (8):
2680--2693(2019)\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2019MS001705.
N. Kimura, M. Kono, and J. Rekimoto. Proceedings of the 2019 CHI Conference on Human Factors in
Computing Systems, Paper 146, page 1--11. New York, NY, USA, Association for Computing Machinery, (May 2019)