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...It allows you to choose an Automatic Differentiation (AD) backend by simply passing an argument to indicate the package to use and automatically generates the efficient derivatives of the objective and constraints while giving you the flexibility to switch between different AD engines as per your problem. Additionally, Optimization.jl takes care of passing problem-specific information to solvers that can leverage it such as the sparsity pattern of the hessian or constraint jacobian and the expression graph.
Package for manifold learning and nonlinear dimensionality reduction
A Julia package for manifold learning and nonlinear dimensionality reduction. Most of the methods use k-nearest neighbors method for constructing local subspace representation. By default, neighbors are computed from a distance matrix of a dataset. This is not an efficient method, especially, for large datasets.
Derives force constants from Gaussian QM for Gromacs MD
...DOI: 10.1007/s00894-017-3530-6
Instruction video:
https://youtu.be/fQVXv8Ge_tg
This Java executable jar derives second order bond force constants for bond stretch and bond angle from quantum mechanical Gaussian calculations. The calculations are compatible with the Amber force field family or any force field derived from the second order tensor of the Hessian from molecular fragments. The output has been made compatible with the Gromacs topology format.
Examples of use include the derivation of bond force constants and equilibrium values for:
-bonded metals in protein active sites
-modified amino acids
-small molecules/drug molecules
A zip of examples files can be found by following the "Browse All Files" link.
...
...The package is more reliable and requires smaller computational time compared with code written only in Matlab. Users need only provide a cost function, gradient function, and the action of the Riemannian Hessian (if a Newton method is used) in Matlab or C++. The package optimizes the function given a set of user-specified parameters, e.g., the domain manifold, algorithm, stopping criterion.
...The base of available algorithms is steadily increasing and includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.
bboss是一个j2ee开源框架,为企业级应用开发提供一站式解决方案,并能有效地支撑移动应用开发。bboss功能涵盖ioc,mvc,jsp自定义标签库,持久层,全局事务托管,安全认证,SSO,web会话共享,cxfwebservice服务发布和管理,hessian服务发布和管理等功能。另外还提供了符合中国式自由流的bboss activiti工作流引擎。在不断的实践过程,越来越多的好东西被吸纳到bboss这个大家庭中,使得bboss能够更好地应用于企业应用项目中,能够更好地解决开发过程中碰到的实际问题。使用bboss提供自动代码生成框架可以更好地提高开发效率。
基于bboss,可以快速地开发构建稳定高效可靠、可扩展、安全的企业级应用系统。
you can find document from
http://yin-bp.iteye.com
Calculates frequencies/modes from an nwchem generated hessian
This is a simple Octave script which calculates the frequencies/normal modes from an nwchem generated hessian matrix. The advantage of having a separate script for this is that you can use the same hessian to calculate frequencies for different isotopic substitutions i.e. you only have to run one nwchem calculation.
The script is finished in its current form in the sense that it is feature complete. Feel free to amend, translate, copy, steal etc.
[NOTE: GO TO https://code.google.com/p/cruelhessian/ TO DOWNLOAD THE LATEST VERSIONS]
Cruel Hessian is an opensource game engine for Soldat. The main purpose of this project is to implement bots AI based on neural networks. Cruel Hessian is programmed in SFML and OpenGL and should work in Linux, Windows and MacOS X.
"HessianCsharp" is a C# library for the Hessian web service protocol. Hessian is a protocol created by Caucho (http://www.caucho.com) and implemented in Java. We offer Hessian under the LGPL for the .NET Environment.
HessianKit is a Framework for Objective-C 2.0 to allow applications for Mac OS X 10.5, and iPhone 2.0 or later to communicate with Hessian web services. The main goals; Be compliant and forgiving, seamless Objective-C experience, and avoid glue-code.
Hessian 1.0.2 implements in Erlang, for simplify writing service module, it provides a erlang behaviour. with hessianerl, you can map request url to module, and map external object to erlang record, all is so easy.
The complete suggestions framework for java, supporting single and multi field suggest, java suggest box, client/server with hessian or json-rpc, and GWT AJAX suggest box, phonetic plugins. Proven high performance for data sets > 1 Mio.
OpenDiscreteDynamicProgrammingTemplate : founds optimal constrainted parameters of a discrete controls with second order optimization template replacing Hessian with directional derivatives and backpropagation for digital filter(as neural network)
It is a lightweight API to invoke web services (RMI, CORBA, WebService (SOAP), XML-RPC, EJB, Hessian, Burlap, REST, ...), how simple Java Object calls. You can integrate Crispy in a Service Oriented Architecture (SOA) or in a Rich Client Platform (RCP).
An Objective-C Framework for the Hessian binary format. The framework provides encoding,decoding Objective-C class mapping support and communication over HTTP on top of Apple's URL Loading System.
HessianPERL, a MOD_PERL Server implementation of the Hessian web services binary protocol created by Caucho (http://www.caucho.com) for the Java platform. This project is relased under the BSD License.