Search Results for "build"

...It has evolved from a single-maintainer project into a collaborative effort, with different contributors stewarding successive year ranges so the collection stays current. The contents skew toward MATLAB and LaTeX, reflecting the tools most winning teams use to build models and typeset their reports; you’ll typically see complete write-ups alongside code that implements optimization, simulation, statistical analysis, or other modeling pipelines.

...On these variants, librsb has been found to be faster than Intel MKL's implementation for CSR. Most numerical kernels code is auto generated, and the supported numerical types can be chosen by the user at build time. librsb implements the Sparse BLAS standard, as specified in the BLAS Forum documents.

mTRF-Toolbox is a MATLAB package for modelling multivariate stimulus-response data, suitable for neurophysiological data such as MEG, EEG, sEEG, ECoG and EMG. It can be used to model the functional relationship between neuronal populations and dynamic sensory inputs such as natural scenes and sounds, or build neural decoders for reconstructing stimulus features and developing real-time applications such as brain-computer interfaces (BCIs). Toolbox Paper: http://dx.doi.org/10.3389/fnhum.2016.00604 Methods Paper: https://doi.org/10.3389/fnins.2021.705621

Riboshape is a suite of algorithms to predict ribosome footprint profile shapes from transcript sequences. It applies kernel smoothing to codon sequences to build predictive features, and uses these features to builds a sparse regression model to predict the ribosome footprint profile shapes. Reference: Liu, T.-Y. and Song, Y.S. Prediction of ribosome footprint profile shapes from transcript sequences. Proceedings of ISMB 2016, Bioinformatics, Vol. 32 No. 12 (2016) i183-i191.

Cell decomposition is one of the first applicable solution for path planning - robot path planning. The algorithm aims to find free areas (cells not occupied by obstacles) in the configuration space, and build a graph of adjacency for these cells.

...The current goal is to make it running out-of-box on multiple platforms. Currently only Linux and Windows are supported. Mac support is possible. The project needs a maintainer for Mac version, since I don't have Mac to build Octclipse and test it on this platform. Also, it is worth to support Eclipse 4.0 Juno with DLTK 4.

Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.