Alternatives and similar repositories for ttpy

Users that are interested in ttpy are comparing it to the libraries listed below

• oseledets / TT-Toolbox
  The git repository for the TT-Toolbox
  ☆211Updated 11 months ago
• Bihaqo / t3f
  Tensor Train decomposition on TensorFlow
  ☆227Updated 4 years ago
• rballester / tntorch
  Tensor Network Learning with PyTorch
  ☆305Updated last year
• PGelss / scikit_tt
  Tensor Train Toolbox
  ☆125Updated 3 months ago
• rballester / tensor_notes
  ☆14Updated 7 years ago
• AndreiChertkov / teneva
  A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays
  ☆59Updated 2 months ago
• rballester / ttrecipes
  Metamodeling, sensitivity analysis and visualization using the tensor train format
  ☆21Updated 3 years ago
• maremun / quffka
  Quadrature-based features for kernel approximation
  ☆16Updated 7 years ago
• izmailovpavel / TTGP
  ☆26Updated 7 years ago
• emstoudenmire / TNML
  Tensor network machine learning. Based on the paper "Supervised Learning with Quantum Inspired Tensor Networks" http://arxiv.org/abs/1605…
  ☆163Updated 6 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆109Updated 8 years ago
• JeanKossaifi / tensorly-notebooks
  Tensor methods in Python with TensorLy
  ☆445Updated 2 years ago
• AndreiChertkov / ttopt
  Gradient-free optimization method for multivariable functions based on the low rank tensor train (TT) format and maximal-volume principle…
  ☆38Updated 2 years ago
• svaiter / pyprox
  Proximal algorithms made easy in Python
  ☆59Updated 9 years ago
• Bihaqo / TensorNet
  ☆141Updated 8 years ago
• mattja / sdeint
  Numerical integration of Ito or Stratonovich SDEs
  ☆169Updated 2 years ago
• mfouesneau / NUTS
  python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011
  ☆131Updated 5 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆184Updated 7 years ago
• gowerrobert / StochOpt.jl
  A suite of stochastic optimization methods for solving the empirical risk minimization problem.
  ☆17Updated 6 years ago
• ebigelow / tf-decompose
  Tensor decomposition implemented in TensorFlow
  ☆63Updated 6 years ago
• JeanKossaifi / ifi-summer-school
  Slides and notebooks for the IfI Summer School 2018 on Machine Learning
  ☆36Updated 7 years ago
• karlnapf / kernel_hmc
  Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"
  ☆26Updated 7 years ago
• cornellius-gp / linear_operator
  A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch
  ☆123Updated this week
• RMT-TheoryAndPractice / RMT
  ☆127Updated 8 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆236Updated last month
• sergeyvoronin / LowRankMatrixDecompositionCodes
  RSVDPACK: Implementations of fast algorithms for computing the low rank SVD, interpolative and CUR decompositions of a matrix, using ran…
  ☆94Updated 3 years ago
• li012589 / NeuralRG
  Pytorch source code for arXiv paper Neural Network Renormalization Group, a generative model using variational renormalization group and …
  ☆81Updated 6 years ago
• anabatsh / PROTES
  Gradient-free optimization method for the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) f…
  ☆38Updated 9 months ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆46Updated 10 years ago
• cjones6 / cubic_reg
  Implementation of Nesterov and Polyak's (2006) cubic regularization algorithm and Cartis et al's (2011) adaptive cubic regularization alg…
  ☆18Updated 3 years ago