• Adam

  • Referenced in 892 articles [sw22205]
  • problems that are large in terms of data and/or parameters. The method is also appropriate ... stationary objectives and problems with very noisy and/or sparse gradients. The hyper-parameters have intuitive...
  • FPINNs

  • Referenced in 27 articles [sw40570]
  • equations (PDEs) based on scattered and noisy data. PINNs employ standard feedforward neural networks...
  • PCL

  • Referenced in 17 articles [sw22770]
  • example, to filter outliers from noisy data, stitch 3D point clouds together, segment relevant parts...
  • FacetNet

  • Referenced in 16 articles [sw20426]
  • Networks. We discover communities from social network data, and analyze the community evolution. These communities ... approach is inappropriate in applications with noisy data. In this paper, we propose FacetNet...
  • ADADELTA

  • Referenced in 59 articles [sw39429]
  • appears robust to noisy gradient information, different model architecture choices, various data modalities and selection...
  • SynLab

  • Referenced in 8 articles [sw25702]
  • noise fluctuations of these transforms on noisy data. A MATLAB package SynLab together with several...
  • denoiseR

  • Referenced in 8 articles [sw17854]
  • Estimate a low rank matrix from noisy data using singular values thresholding and shrinking functions...
  • CUBGCV

  • Referenced in 8 articles [sw04346]
  • cubic smoothing spline fitted to n noisy data points, with the degree of smoothing chosen...
  • PDE-Net

  • Referenced in 63 articles [sw36963]
  • initial attempt to learn evolution PDEs from data. Inspired by the latest development of neural ... relatively long time, even in a noisy environment...
  • RBoost

  • Referenced in 3 articles [sw29975]
  • AdaBoost tends to overfit to the noisy data in many applications. Accordingly, improving the antinoise ... many applications. The sensitiveness to the noisy data of AdaBoost stems from the exponential loss ... which are more robust to the noisy data compared with AdaBoost. RBoost1 and RBoost2 optimize ... when the training data sets contain noisy data...
  • GenSoFNN

  • Referenced in 9 articles [sw08761]
  • analysis is first performed on the training data and the fuzzy rules are subsequently derived ... defined node operations; (3) susceptibility to noisy training data and the stability-plasticity dilemma...
  • PersistenceImages

  • Referenced in 35 articles [sw41418]
  • noisy sampling of an underlying space, and tools from topological data analysis can characterize this...
  • FHEW

  • Referenced in 23 articles [sw14880]
  • required to refresh noisy ciphertexts and keep computing on encrypted data. Bootstrapping in the latest...
  • PyDMD

  • Referenced in 4 articles [sw38466]
  • underlying system. See Kutz (”Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems ... others, in order to deal with noisy data, big dataset, or spurious data for example...
  • HeartPy

  • Referenced in 3 articles [sw30799]
  • Analysing Noisy Driver Physiology Real-Time Using Off-the-Shelf Sensors: Heart Rate Analysis Software ... rate analysis toolkit designed for photoplethysmogram (PPG) data. Most openly available algorithms focus on electrocardiogram ... function well on PPG data, especially noisy PPG data collected in experimental studies. To counter...
  • SINDy-PI

  • Referenced in 3 articles [sw40367]
  • approach to discover dynamical systems models from data. Although extensions have been developed to identify ... conservation laws from limited and noisy data. In particular, we show that the proposed approach...
  • QUB

  • Referenced in 3 articles [sw22010]
  • most likely transition rates from noisy data. QUB was created to solve problems...
  • FPDclustering

  • Referenced in 3 articles [sw15462]
  • with non-spherical clusters, outliers, or noisy data. Facto PD-clustering (FPDC) is a recently...
  • Rubik

  • Referenced in 2 articles [sw30094]
  • leverage a vast amount of labeled EHR data for phenotype discovery. However, existing unsupervised phenotyping ... cannot directly handle missing, or noisy data. We propose Rubik, a constrained non-negative tensor ... significantly alleviate the impact of noisy and missing data. We utilize the Alternating Direction Method...
  • YANA

  • Referenced in 4 articles [sw35556]
  • often not known. As such data are noisy, YANA features a fast evolutionary algorithm ... minimum error, including alerts for inconsistent experimental data. We offer the possibility to include further...