• SINDy

  • Referenced in 31 articles [sw30277]
  • dynamics (SINDy) is a recently proposed data-driven modelling framework that uses sparse regression techniques...
  • np

  • Referenced in 111 articles [sw10543]
  • mean regression models and parametric quantile regression models, among others. The np package focuses ... discrete, and categorical data often found in applied settings. Data-driven methods of bandwidth selection...
  • TPVM

  • Referenced in 9 articles [sw03347]
  • message-passing model; (b) a data-driven instantiation model that enables straightforward specification of computation...
  • CANN

  • Referenced in 6 articles [sw41756]
  • general approach to predictive data-driven constitutive modeling by deep learning. In this paper ... novel machine learning architecture for data-driven modeling of the mechanical constitutive behavior of materials...
  • PyDMD

  • Referenced in 5 articles [sw38466]
  • uses Dynamic Mode Decomposition for a data-driven model simplification based on spatiotemporal coherent structures ... model reduction algorithm developed by Schmid (see ”Dynamic mode decomposition of numerical and experimental data ... high-fidelity measurements, like experimental data and numerical simulations, so it is an equation-free ... system. See Kutz (”Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems”) for a comprehensive...
  • SCAPE

  • Referenced in 28 articles [sw19408]
  • PEople)---a data-driven method for building a human shape model that spans variation...
  • 3DMatch

  • Referenced in 6 articles [sw32561]
  • this paper, we present 3DMatch, a data-driven model that learns a local volumetric patch...
  • QuantGAN

  • Referenced in 5 articles [sw42448]
  • GANs: Deep Generation of Financial Time Series. Modeling financial time series by stochastic processes ... alternative, we introduce Quant GANs, a data-driven model which is inspired by the recent...
  • CAPUSHE

  • Referenced in 62 articles [sw13365]
  • Slope heuristics: overview and implementation. Model selection is a general paradigm which includes many statistical ... have proposed a promising data-driven method to calibrate such criteria whose penalties are known...
  • MOSSFARM

  • Referenced in 2 articles [sw02750]
  • structure selection are very important for data-driven modeling, data mining, and system identification tasks...
  • MLMOD

  • Referenced in 1 article [sw39711]
  • MLMOD Package: Machine Learning Methods for Data-Driven Modeling in LAMMPS. We discuss a software ... package for incorporating into simulations data-driven models trained using machine learning methods. These...
  • decon

  • Referenced in 22 articles [sw11088]
  • function from contaminated data; (2) nonparametric regression model with errors-in-variables. The R functions ... data to the deconvolution kernel estimation. Several methods for the selection of the data-driven ... Deconvolution estimation in measurement error models: The R package decon. Journal of Statistical Software...
  • ResLogit

  • Referenced in 1 article [sw42492]
  • residual neural network logit model for data-driven choice modelling. This paper presents a novel ... model formulation seamlessly integrates a Deep Neural Network (DNN) architecture into a multinomial logit model ... shown remarkable success in modelling complex and noisy behavioural data. However, econometric studies have argued ... choice analysis.We develop a data-driven choice model that extends the systematic utility function...
  • svars

  • Referenced in 1 article [sw38309]
  • Data-Driven Identification of SVAR Models. Implements data-driven identification methods for structural vector autoregressive ... /jss.v097.i05>. Based on an existing VAR model object (provided by e.g. VAR() from the ’vars ... structural impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon...
  • DeepAdverserialRegulariser

  • Referenced in 16 articles [sw42064]
  • model-based methods. Among those variational regularization models are one of the most popular approaches ... propose a new framework for applying data-driven approaches to inverse problems, using a neural...
  • BioPreDyn-bench

  • Referenced in 2 articles [sw29329]
  • suite of benchmark problems for dynamic modelling in systems biology. BioPreDyn-Bench has been developed ... BioPreDyn partners are developing data-driven computational models to analyze multi-scale biological networks, creating...
  • Distil

  • Referenced in 1 article [sw37878]
  • Distil: A Mixed-Initiative Model Discovery System for Subject Matter Experts. We present in-progress ... with subject matter expertise to generate data-driven models using an interactive analytic question first...
  • CoPro

  • Referenced in 1 article [sw37594]
  • CoPro: a data-driven modelling framework for conflict risk projections. In light of predicted shifts...
  • ShapeNet

  • Referenced in 17 articles [sw35059]
  • providing many semantic annotations for each 3D model such as consistent rigid alignments, parts ... interface to enable data visualization of object attributes, promote data-driven geometric analysis, and provide ... indexed more than 3,000,000 models, 220,000 models out of which are classified...
  • emgr

  • Referenced in 15 articles [sw07554]
  • have wide-spread use, for example in: model reduction, decentralized control, optimal placement, sensitivity analysis ... nonlinear systems due to their data-driven computation. The empirical Gramian framework is a compact...