• DeepXDE

  • Referenced in 38 articles [sw32456]
  • learning library for solving differential equations. Deep learning has achieved remarkable success in diverse applications ... more rapid development of the emerging Scientific Machine Learning field...
  • NeuralPDE.jl

  • Referenced in 33 articles [sw39548]
  • solvers for partial differential equations using scientific machine learning (SciML) techniques such as physics-informed...
  • SMAC

  • Referenced in 79 articles [sw27215]
  • effective for the hyperparameter optimization of machine learning algorithms, scaling better to high dimensions ... designers focus on tasks that are more scientifically valuable than parameter tuning...
  • ModelingToolkit.jl

  • Referenced in 2 articles [sw41449]
  • numeric computation in scientific computing and scientific machine learning. It then mixes ideas from symbolic...
  • MLxtend

  • Referenced in 3 articles [sw29046]
  • extensions to Python’s scientific computing stack. Mlxtend (machine learning extensions) is a Python library...
  • ODE.jl

  • Referenced in 1 article [sw34620]
  • basic Ordinary Differential Equation solvers for scientific machine learning (SciML). Various basic Ordinary Differential Equation...
  • ParaDRAM

  • Referenced in 2 articles [sw35226]
  • integration of mathematical objective functions encountered in scientific inference. ParaDRAM is currently accessible from several ... efficiently solve a variety of machine learning and scientific inference problems on a wide range...
  • DeepHyper

  • Referenced in 4 articles [sw41119]
  • design and development of machine learning (ML) models for scientific and engineering applications. DeepHyper reduces...
  • Orbital library

  • Referenced in 13 articles [sw05562]
  • search and planning, as well as machine learning algorithms. Generally speaking, the conceptual idea behind ... components that surround the heart of many scientific applications, hence the name ”Orbital library...
  • ParaMonte

  • Referenced in 1 article [sw35224]
  • Bayesian models in data science, Machine Learning, and scientific inference, with the design goal...
  • DiffEqFlux

  • Referenced in 7 articles [sw27559]
  • discuss the complementary nature between machine learning models and differential equations. We demonstrate the ability ... scientific computing field to be readily applied to the challenges posed by machine learning...
  • JMLR MLOSS

  • Referenced in 1 article [sw14408]
  • trivial machine learning algorithms, toolboxes or even languages for scientific computing...
  • mlpy

  • Referenced in 2 articles [sw12848]
  • module for Machine Learning built on top of NumPy/SciPy and the GNU Scientific Libraries. mlpy ... wide range of state-of-the-art machine learning methods for supervised and unsupervised problems...
  • TensorDiffEq

  • Referenced in 1 article [sw39549]
  • introducing domain-aware deep machine learning models into scientific computation. Several software suites have emerged...
  • mcfly

  • Referenced in 2 articles [sw37867]
  • scientific community, but for researchers with no or limited machine learning experience...
  • GemPy

  • Referenced in 5 articles [sw31288]
  • geological models and additional assets for advanced scientific investigations. These assets provide the full power ... they enable the link to machine-learning and Bayesian inference frameworks and thus a path ... summary, we provide a basis for open scientific research using geological models, with...
  • BLISlab

  • Referenced in 1 article [sw16637]
  • great importance to scientific computing and, increasingly, machine learning. It is a simple enough concept...
  • GPUMLib

  • Referenced in 3 articles [sw13694]
  • Machine Learning Library (GPUMLib) that aims to provide the building blocks for the scientific community...
  • libcmaes

  • Referenced in 2 articles [sw28976]
  • industrial and scientific applications, to the solving of reinforcement and machine learning problems...