357 skills found · Page 3 of 12
joeydumont / Complex BesselA C++ library to evaluate Bessel functions of all kinds.
joergoster / Stockfish NNUEUCI Chess engine Stockfish with an Efficiently Updatable Neural-Network-based evaluation function
NVIDIA / When2CallA dataset for training and evaluating LLMs on decision making about "when (not) to call" functions
nasa / Prog AlgsThe Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and perform estimation and prediction functions. The library allows the rapid development of prognostics solutions for given models of components and systems. Different algorithms can be easily swapped to do comparative studies and evaluations of different algorithms to select the best for the application at hand.
edxmorgan / Casadi On Gputurn CasADi function into GPU ready kernels so large batches of function evaluations can run in parallel at high speed [𝐏𝐲𝐭𝐨𝐫𝐜𝐡 & 𝐂𝐮𝐩𝐲 𝐜𝐨𝐦𝐩𝐚𝐭𝐢𝐛𝐥𝐞]
awslabs / Aws Lambda Security ControlsThis is a collection of AWS CloudFormation templates which create Lambda functions triggered by CloudWatch Events rule to evaluate AWS API calls to trigger Amazon Simple Notification Service (Amazon SNS) for notifications.
suryakiranmg / Dynamic Movement Primitives And Imitation Learning RoboticsDynamic movement primitives (DMPs) are a method of trajectory control/planning from Stefan Schaal’s lab. Complex movements have long been thought to be composed of sets of primitive action ‘building blocks’ executed in sequence and \ or in parallel, and DMPs are a proposed mathematical formalization of these primitives. The difference between DMPs and previously proposed building blocks is that each DMP is a nonlinear dynamical system. The basic idea is that you take a dynamical system with well specified, stable behavior and add another term that makes it follow some interesting trajectory as it goes about its business. The DMP differential equations (Transformation System, Canonical System, Non-linear Function) realize a general way of generating point-to-point movements. Imitation learning using linear regression is performed to compute the weight factor W from a demonstrated trajectory dataset, given by a teacher. The quality of the imitation is evaluated by comparing the training data with the data generated by the DMP.
sigopt / EvalsetBenchmark suite of test functions suitable for evaluating black-box optimization strategies
rode / RodeRode facilitates Automated Governance in your software supply chain. This repository contains the rode API which is the primary interface between the rode UI or rode Collectors and metadata storage in Grafeas. The rode API provides functions for metadata search and storage as well as policy creation and evaluation.
mahdi-usask / Wind Speed Forecasting For Wind Power Generation Plant. Neural Network ML Based Prediction Algo. For largescale wind power penetration Wind speed prediction is a basic requirement of wind energy generation. There are many artificial neural network (ANN), ARMA, ARIMA approaches proposed in the recent literature in order to tackle this problem. This paper will use the artificial neural network (ANN) approach to get a prediction of wind speed using historical wind speed data. The historical data used here were gathered from NREL website ,as hourly basis from 80 meter hub height. The measurement location is NREL Flatirons Campus (M2). The readings displayed are derived from instruments mounted on or near a 82 meter (270 foot) meteorological tower located at the western edge of the Flatirons Campus (formerly NWTC) and about 11 km (7 miles) west of Broomfield, and approximately 8 km (5 miles) south of Boulder, Colorado. The tower is located at 39o 54' 38.34" N and 105o 14' 5.28" W (datum WGS84) with its base at an elevation of 1855 meters (6085 feet) above mean sea level. Data from year 2014 to 2018, in total 5 years of data has been used here as dataframe. Here the neural network has been implemented by Tensorflow’s Keras API. The used model is “sequential”. Four dense layer has been used in the optimized model. LSTM(Long- short-term memory) architecture has been used here as neural network architecture. Activation function being used in the dense layers are dropout function. The optimizer being used here is Adam. Here various range of Dropout function has been examined and chosen the best fit for this model. Also this paper examined various kinds of optimization method and used the best fitted one. The model performances were evaluated using the mean squared error using adam optimizer. Various kinds of data analytic techniques has been used here for better visualization and in depth understanding of the dataset and its variables. Since it is mostly a time series data so in the analytic part how the data is being changed with time has been shown. From the result of the predicted dataset it can be state that, this wind speed prediction model works best for all kinds of winds speed besides overfitted/ abnormal wind speeds which is a very rare case scenario.
bwiernik / PipebindFlexible binding for complex function evaluation with the Base R |> pipe
wavefunction91 / GauXCGauXC is a modern, modular C++ library for the evaluation of quantities related to the exchange-correlation (XC) energy (e.g. potential, etc) in the Gaussian basis set discretization of Kohn-Sham density function theory (KS-DFT) on heterogenous architectures.
giabaio / SurvHESurvival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.
crlandsc / Torch Log WmselogWMSE, an audio quality metric & loss function with support for digital silence target. Useful for training and evaluating audio source separation systems.
PARMAGroup / UNet Instance Cell Segmentation[Pytorch] This project aims to perform well at instance segmentation on the BBBC006 cells dataset. We tested UNet over several configurations including the loss function, evaluation function and the datasets.
encryptogroup / UCImplementation of Valiant's universal circuit construction optimized for private function evaluation
cwickham / Advanced ROne day course covering functions, functional programming and tidy evaluation
p7s1digital / Oasis Jsbridge AndroidEvaluate JavaScript code and map values, objects and functions between Kotlin/Java and JavaScript on Android.
rok-cesnovar / Stan DistributionsA web app to visualize distributions in Stan. Uses Stan Math C++ compiled to Webassembly to evaluate the functions using actual Stan implementations. Uses d3.js for visualizations.
3003 / Text Retrieval PythonCollection of functions and scripts for text retrieval in Python: Document collection preprocessing, Feature Selection, Indexing, Query processing, Ranking, Relevance evaluation
