Search Results for "level set methods"

The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. ...

Version 2.5 is available! The latest changes are in TFastList class. It is the secondary class intended for fast string managment. The newest TGraph component is available as well. The new ParseUtils.FindFormula method allows searching any of possible formulas within some text. Parse components are intended for Delphi developers and perform high-speed (about 10 million evaluations per second) mathematics and boolean calculations. All components are available for Delphi 6, Delphi 7,...

...We create a distributed system with Apache thrift and the C-API of glpk. Now, it is possible to use as many cores in a network as you want. With a focus on the MILP methods we implement a load balancing and speed up the solving process in a multiplicative way. Sometimes we have super-linear speedup with a small set of hardware. With a splitting of problems, parallel computing and distributing the actual best solution to all running processes we solve CBP much faster than a sequential processing can do.

GRaPe - a platform-independent software tool for building integrative gene-reaction-protein (GRP) networks. It generates the kinetic equations for each reaction and outputs a SBML document. It also implements two methods for parameter estimation.