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A library for probabilistic modeling, inference, and criticism. Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets. Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It...

MASyV (Multi-Agent System Visualization) enables one to write agent-based models/cellular automata, eg. in C, visualize them in real time & capture to movie file with MASyVs GUI & message passing lib. Includes examples: Hello World, ants, viral infection

The Sequence Diagram / MSC Generator is a tool to generate Sequence Diagrams from a textual description. The diagrams (bmp, png, wmf, and emf) are conform to UML2 standard (Sequence Diagrams) und to SDL standard (Message Sequence Chart).

The Location Containment Object Model(LCOM) is a simulation framework written in Python. LCOM provides a rule-based solution to handling partial object containment, object migration, message passing, and simulation observation.