• MTS

  • Referenced in 4 articles [sw15485]
  • models, copula-based volatility models, and low-dimensional BEKK models. The package also considers multiple...
  • NMPC

  • Referenced in 2 articles [sw06445]
  • approach is proposed to implement low-dimensional parameterized Nonlinear Model Predictive Control (NMPC) schemes...
  • OpenKE

  • Referenced in 2 articles [sw30611]
  • various fundamental models to embed knowledge graphs into a continuous low-dimensional space. OpenKE prioritizes...
  • RPtests

  • Referenced in 0 articles [sw19531]
  • tests for both high and low-dimensional linear models. It can test for a variety...
  • hdm

  • Referenced in 4 articles [sw21313]
  • low-dimensional causal/ structural parameters are provided which appear in high-dimensional approximately sparse models...
  • ProjE

  • Referenced in 2 articles [sw34444]
  • developed using low-dimensional graph embeddings. Although researchers continue to improve these models using...
  • persona2vec

  • Referenced in 1 article [sw33469]
  • Graphs. Graph embedding techniques, which learn low-dimensional representations of a graph, are achieving state ... model while achieving better performance. Graph embedding techniques, which learn low-dimensional representations ... than the existing state-of-the-art model while achieving better performance...
  • FMS

  • Referenced in 7 articles [sw31728]
  • inliers drawn around a low-dimensional subspace of a higher dimensional ambient space ... stationary point. Further, under a special model of data, FMS converges to a point which...
  • Active subspaces

  • Referenced in 3 articles [sw32976]
  • emerging set of tools for discovering low-dimensional structure in a given function of several ... function is the map from the physical model’s input parameters to its output quantity...
  • Charagram

  • Referenced in 1 article [sw26535]
  • simple approach for learning character-based compositional models to embed textual sequences. A word ... single nonlinear transformation to yield a low-dimensional embedding. We use three tasks for evaluation...
  • Graph Investigator

  • Referenced in 2 articles [sw26160]
  • similarity by embedding graph patterns into low-dimensional space or distance measurement based on feature ... network evolving in the process of angiogenesis, modelled with the use of cellular automata...
  • ALPS MPS

  • Referenced in 1 article [sw19924]
  • physics as well as dynamics of low-dimensional quantum systems. In this paper, we present ... arbitrary one-dimensional and two-dimensional models. Implementing the conservation of quantum numbers for generic...
  • ManiSolve

  • Referenced in 1 article [sw34623]
  • Five decades of numerical experience show that models of technical systems tend to decompose favorably ... that of solving a sequence of low-dimensional ones. The most serious weakness of this...
  • LFADS

  • Referenced in 0 articles [sw16550]
  • single-trial, high-dimensional neural spiking data. LFADS is a sequential model based ... observed spiking to a set of low-dimensional temporal factors, per-trial initial conditions...
  • VariableScreening

  • Referenced in 0 articles [sw15948]
  • varying coefficient longitudinal models with ultra- high dimensional predictors <http://imstat.org/aoas/next_issue.html>. The effect ... vary over time, approximated by a low-dimensional B-spline. Within-subject correlation is handled...
  • EEBoost

  • Referenced in 1 article [sw26353]
  • prediction in standard regression problems. However, simple models may misspecify or fail to capture important ... applied in high-dimensional settings where inference for low-dimensional parameters would typically be based...
  • DiSMEC

  • Referenced in 1 article [sw30154]
  • embedding the label matrix to a low-dimensional linear sub-space. However, in the presence ... diverse label spaces, structural assumptions such as low rank can be easily violated. In this ... coupled with explicit capacity control to control model size. Unlike most state...
  • MOTIF-EM

  • Referenced in 1 article [sw16892]
  • technique works by constructing rotationally invariant, low-dimensional representations of local regions in the input ... also been used to build atomic models for some maps. We also used MOTIF...
  • SINE

  • Referenced in 1 article [sw32344]
  • Attributed network embedding aims to learn low-dimensional vector representations for nodes in a network ... formulates a probabilistic learning framework that separately models pairs of node-context and node-attribute...
  • GAP

  • Referenced in 2735 articles [sw00320]
  • GAP is a system for computational discrete algebra...