• hgam

  • Referenced in 73 articles [sw11201]
  • smoothness penalty for high-dimensional generalized additive models. The combination of sparsity and smoothness ... estimator for high dimensional but sparse additive models. Finally, an adaptive version of our sparsity...
  • pacbpred

  • Referenced in 4 articles [sw07805]
  • Bayesian Estimation and Prediction in Sparse Additive Models. This package is intended to perform estimation ... prediction in high-dimensional additive models, using a sparse PAC-Bayesian point of view ... Bayesian Estimation and Prediction in Sparse Additive Models’, Electronic Journal of Statistics...
  • SMART_

  • Referenced in 33 articles [sw04097]
  • model-checking algorithms, are available. For the study of stochastic and timing behavior, both sparse ... underlying process is a Markov chain. In addition, discrete-event simulation is always applicable regardless ... process, but certain classes of non-Markov models can still be solved numerically. Finally, since...
  • Spatial Statistics

  • Referenced in 8 articles [sw06026]
  • spatially autoregressive (MRSA) models. In addition, it contains code for creating sparse spatial weight matrices...
  • refund

  • Referenced in 54 articles [sw07434]
  • decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based ... variability are constructed. Standard mixed model representations of functional expansions are used to construct curve ... decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution ... simulation studies that include both densely and sparsely observed functions. We apply our method...
  • pgraph

  • Referenced in 1 article [sw33627]
  • Both lasso and sparse additive model projections are implemented. Both Pearson correlation and distance covariance...
  • SimpleMKL

  • Referenced in 63 articles [sw12290]
  • formulation with an additional constraint on the weights that encourages sparse kernel combinations. Apart from ... based on wavelet kernels and on some model selection problems related to multiclass classification problems...
  • MESS

  • Referenced in 23 articles [sw14886]
  • MATLAB. It is intended for solving large sparse matrix equations. The new version has been ... upgrades in the Matlab releases since 2000. Additionally new solvers for differential Riccati equations extend ... solve Lyapunov and Riccati equations, and do model reduction. Even though MESS has been implemented...
  • Glmnet

  • Referenced in 10 articles [sw25026]
  • multinomial regression, Poisson regression and the Cox model. Features include: high efficiency by using coordinate ... sparse input-matrix formats and range constraints on coefficients. Two recent additions are the multiresponse...
  • k-Wave

  • Referenced in 27 articles [sw07387]
  • three dimensions. The simulation functions can additionally be used as a flexible time reversal image ... toolbox are described, and several novel modeling examples are given. First, the use of data ... when the measurement surface has only a sparse array of detector points. Second, by comparison...
  • BDgraph

  • Referenced in 12 articles [sw14815]
  • Bayesian structure learning in sparse Gaussian graphical models. Decoding complex relationships among large numbers ... approach to this problem is Gaussian graphical modeling, which describes conditional independence of variables through ... efficient Bayesian framework for Gaussian graphical model determination which is a trans-dimensional Markov Chain ... studies to show its empirical usefulness. In addition, we implemented the method...
  • 2LEV-D2P4

  • Referenced in 9 articles [sw00009]
  • PSBLAS library for sparse matrix computations. The package, named 2LEV-D2P4 (Two-LEVel Domain Decomposition ... PSBLAS), currently includes various versions of additive Schwarz preconditioners that are combined with a coarse ... large-scale linear systems arising from model problems and real applications, showing its effectiveness...
  • Exa-Dune

  • Referenced in 11 articles [sw32962]
  • oriented numerical methods have included GPU-based sparse approximate inverses, matrix-free sum-factorisation ... matrix-free preconditioners. On top of that, additional scalability is facilitated by exploiting massive coarse ... concepts are applied in a land-surface model including subsurface flow and surface runoff...
  • Toast++

  • Referenced in 4 articles [sw14492]
  • libraries written in C++ for sparse linear algebra, finite element computation, and nonlinear image reconstruction ... forward modelling and inverse solution are included. Users who need additional functionality can write their...
  • LinearCovarianceModels.jl

  • Referenced in 2 articles [sw37838]
  • case as well as special models (e.g., Toeplitz, sparse, trees) that are of interest ... maxima can thus be computed reliably. In addition we identify several scenarios for which...
  • RKHSMetaMod

  • Referenced in 1 article [sw28872]
  • Sparse Optimization Problem based on the Reproducing Kernel Hilbert Spaces (RKHS). The estimated meta model ... additive model that satisfies the properties of the Hoeffding decomposition, and its terms estimate...
  • iDUDE

  • Referenced in 4 articles [sw21734]
  • estimated from a large collection of sparse statistics, resulting in poor estimates that would ... basic DUDE scheme by incorporating statistical modeling tools that have proven successful in addressing similar ... iDUDE, are described for examples of additive and nonadditive noise. The resulting denoisers significantly surpass...
  • Cornac

  • Referenced in 3 articles [sw35444]
  • addition to core utilities for accessing, building, evaluating, and comparing recommender models, Cornac is distinctive ... putting emphasis on recommendation models that leverage auxiliary information in the form of a social ... ratings, clicks), which tend to be sparse in practice. To facilitate broad adoption and community...
  • LinCE

  • Referenced in 1 article [sw39136]
  • code-switched languages. In addition, it is unclear whether a model architecture is applicable ... lack of a centralized benchmark and the sparse corpora that researchers employ based on their ... real-time. In addition, we provide the scores of different popular models, including LSTM, ELMo...
  • pylearn-simulate

  • Referenced in 1 article [sw26392]
  • perform an analysis in which the computed model can be linked to a given structure ... linear regression problems with sparse and structured penalties. Additionally, this approach allows the user ... data without taking into account the actual model that will be fit to the data...