Search Results for "graphs"

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. ...

...The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). TensorFlow expresses its computations as dataflow graphs, with each node in the graph representing an operation. Nodes take tensors—multidimensional arrays—as input and produce tensors as output. The framework allows for these algorithms to be run in C++ for better performance, while the multiple levels of APIs let the user determine how high or low they wish the level of abstraction to be in the models produced. ...

Use Keras models in C++ with ease. A lightweight header-only library for using Keras (TensorFlow) models in C++. Works out-of-the-box also when compiled into a 32-bit executable. (Of course, 64 bit is fine too.) Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can...

...Several types of hash tables are implemented: separated chaining, open adressing with linear probing and double function hash; this last one has a garbage colector mechanism that allows to free deleted entries. Dynamic linear hash tables are implemented too. The main algorithms on graphs are implemented in an easy way and with good performance features. Network Flow (maximum and min cost), cut points, topological sort, spanning trees, min paths. etc. The graphs are generic in the sense that they can contain data independent of the algorithm. Several containers of the C++ STL library are implemented with Aleph-w. ...

...It is organized as a study and reference collection for algorithm practice, technical interview preparation, and problem-solving review. The repository includes implementations for many classic coding challenge categories such as arrays, strings, linked lists, trees, graphs, dynamic programming, sorting, searching, and math. It is useful for comparing approaches, reviewing solution patterns, and studying how common interview problems can be implemented in code. Because it is a solution archive, it is best used as a learning companion after attempting problems independently. Its main value is providing a broad, accessible reference set for developers preparing for coding interviews.

The libRSF is an open source C++ library that provides several components that are required to estimate the state of a (robotic) system based on probabilistic methods. By applying the factor graph concept, well known from Graph SLAM, libRSF provides a robust solution for many sensor fusion problems. The general idea of factor graphs is to describe the state estimation problem as a graph of nodes (the state variables) that are connected by factors (measurements). The resulting graph optimization problem can be solved by applying non-linear least squares optimization.

As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. ...

LSGTL means LLX’s Static Graph Template Library which is a light-weighted header-only template library developed mainly for static graph analysis. LSGTL is expected to be used in laboratories for research purposes mostly.