• PETSc

  • Referenced in 1584 articles [sw04012]
  • Computation (PETSc) is a suite of data structures and routines that provide the building blocks ... users it initially has a much steeper learning curve than a simple subroutine library...
  • Fashion-MNIST

  • Referenced in 49 articles [sw31842]
  • learning algorithms, as it shares the same image size, data format and the structure...
  • Rseslib

  • Referenced in 16 articles [sw30225]
  • rough set and machine learning algorithms and data structures in Java. It provides algorithms...
  • graph2vec

  • Referenced in 10 articles [sw32340]
  • Graphs. Recent works on representation learning for graph structured data predominantly focus on learning distributed...
  • MULAN

  • Referenced in 65 articles [sw08062]
  • Java library for learning from multi-label data. It offers a variety of classification, ranking ... well as algorithms for learning from hierarchically structured labels. In addition, it contains an evaluation...
  • SynTReN

  • Referenced in 17 articles [sw12311]
  • synthetic gene expression data for design and analysis of structure learning algorithms. Background: The development ... infer the structure of gene regulatory networks based on expression data is an important subject ... benchmark data sets for which the underlying network is known. Since experimental data sets ... well-characterized synthetic data sets that allow thorough testing of learning algorithms in a fast...
  • RCV1

  • Referenced in 123 articles [sw07279]
  • corrected data as RCV1-v2. We benchmark several widely used supervised learning methods on RCV1 ... versions of the category assignments and taxonomy structures, via online appendices...
  • bnlearn

  • Referenced in 77 articles [sw08265]
  • Search) and hybrid (MMHC and RSMAX2) structure learning algorithms for both discrete and Gaussian networks ... utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced...
  • bnstruct

  • Referenced in 4 articles [sw29260]
  • package bnstruct: Bayesian Network Structure Learning from Data with Missing Values. Bayesian Network Structure Learning ... Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu...
  • SchNet

  • Referenced in 9 articles [sw40890]
  • ideally suited to learn representations for structured data and speed up the exploration of chemical ... first choice for images, audio and video data, the atoms in molecules are not restricted ... model local correlations without requiring the data to lie on a grid. We apply those ... layers in SchNet: a novel deep learning architecture modeling quantum interactions in molecules. We obtain...
  • PointNet

  • Referenced in 43 articles [sw31209]
  • PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. Point cloud ... important type of geometric data structure. Due to its irregular format, most researchers transform such...
  • NLTK

  • Referenced in 40 articles [sw00626]
  • everyday communication by humans. The reader will learn how to write Python programs that work ... text. A comprehensive range of linguistic data structures is presented as well as algorithms...
  • Gudhi

  • Referenced in 38 articles [sw08777]
  • structures for computational topology. An application of interest for computational topology is topological data analysis ... where one is interested in learning topological invariants of a shape, sampled by a point ... implemented with a simplex tree data structure. The simplex tree is an efficient and flexible...
  • bmrm

  • Referenced in 23 articles [sw11016]
  • machine learning which make it powerful for big data analysis. The applications includes: structured prediction...
  • Daikon

  • Referenced in 44 articles [sw04319]
  • machine learning technique that can be applied to arbitrary data. Daikon can detect invariants ... Java, and Perl programs, and in record-structured data sources; it is easy to extend...
  • BDgraph

  • Referenced in 18 articles [sw14815]
  • practice, sensible approach for structure learning. We illustrate the efficiency of the method ... broad range of simulated data. We then apply the method on large-scale real applications...
  • PcGive

  • Referenced in 50 articles [sw04927]
  • Professionaltm aims to give an operational and structured approach to econometric modelling using the most ... textbooks’ and `computer manuals’ by linking the learning of econometric methods and concepts ... divided by the type of data to which they are (usually) applied. The documentation...
  • RolX

  • Referenced in 8 articles [sw32343]
  • have similar structural behavior. Roles should be automatically determined from the data, and could ... edges), unsupervised learning approach for automatically extracting structural roles from general network data. We demonstrate ... mining tasks: from exploratory data analysis to network transfer learning. Moreover, we compare network role...
  • UMAP

  • Referenced in 30 articles [sw34900]
  • Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed ... scalable algorithm that applies to real world data. The UMAP algorithm is competitive with ... arguably preserves more of the global structure with superior run time performance. Furthermore, UMAP ... general purpose dimension reduction technique for machine learning...