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Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make...

An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging...

- - - T H I S P R O J E C T M O V E D T O G I T H U B - - - A framework for the implementation of advanced real-time control systems which uses signal/block-based schematics (like Simulink) extended by several features like state machines and online-exchangeable sub-simulations. Besides, this framework properly handles multiple threads, their communication, allows to synchronise control systems to external events (e.g. variable timers or incoming network packages) and provides many other nice features. ...

...StochKit is part of the StochSS project [http://www.stochss.org/], and we are relying on continued funding for sustained development. Please consider registering to show your support. Register here: https://docs.google.com/forms/d/12tAH4f8CJ-3F-lK44Q9uQHFio_mGoK0oY829q5lD7i4/viewform GillesPy is a python interface for developing models and simulating them with StochKit. Please see: https://github.com/GillesPy/gillespy/ StochKit currently supports Linux, Windows, and OS X.