Alternatives and similar repositories for newton-sketch

Users that are interested in newton-sketch are comparing it to the libraries listed below

• mikigom / large-scale-OT-mapping-TF
  Tensorflow Implementation of "Large-scale Optimal Transport and Mapping Estimation"(ICLR2018/NIPS 2017 OTML)
  ☆20Updated 7 years ago
• jayanthkoushik / torch-gel
  Group elastic net implementation in PyTorch.
  ☆46Updated 5 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆91Updated 7 years ago
• BiuBiuBiLL / NPEET_LNC
  local non-uniformity correction for mutual information estimation
  ☆71Updated 4 years ago
• gpeyre / 2016-ICML-gromov-wasserstein
  Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.
  ☆75Updated 9 years ago
• thalitadru / LDMnet-pytorch
  Implementation of LDMnet in pytorch
  ☆22Updated 7 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• josipd / torch-two-sample
  A PyTorch library for two-sample tests
  ☆241Updated last month
• arolet / wasserstein-dictionary-learning
  A matlab toolbox to perform Wasserstein Dictionary Learning or NMF
  ☆32Updated 9 years ago
• mctorch / mctorch
  A manifold optimization library for deep learning
  ☆250Updated 4 years ago
• gowerrobert / StochOpt.jl
  A suite of stochastic optimization methods for solving the empirical risk minimization problem.
  ☆17Updated 6 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• SheffieldML / vargplvm
  Bayesian GPLVM in MATLAB and R
  ☆76Updated 8 years ago
• ryotat / dal
  Dual Augmented Lagrangian (DAL) algorithm for sparse/low-rank reconstruction and learning
  ☆34Updated 10 years ago
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 6 years ago
• danielkunin / Regularized-Linear-Autoencoders
  Loss Landscapes of Regularized Linear Autoencoders
  ☆147Updated 3 years ago
• mijungi / lllvm
  ☆17Updated 10 years ago
• jjfeng / spinn
  Sparse-input neural networks
  ☆23Updated 2 years ago
• adler-j / wasserstein_inverse_problems
  Code for the article "Learning to solve inverse problems using Wasserstein loss"
  ☆28Updated 8 years ago
• LCSL / FALKON_paper
  FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"
  ☆30Updated 5 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆51Updated 4 years ago
• audeg / StochasticOT
  Stochastic Optimization for Optimal Transport
  ☆22Updated 9 years ago
• judyboon / BASS
  A Bayesian group factor model with structured sparsity
  ☆22Updated 9 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• devmotion / CalibrationPaper
  Repository of NeurIPS 2019 paper "Calibration tests in multi-class classification: A unifying framework"
  ☆17Updated 4 years ago
• MinhyungCho / riemannian-batch-normalization-pytorch
  Riemannian approach to batch normalization
  ☆22Updated 8 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆46Updated 7 years ago
• felixyu / SRF
  Spherical random features for polynomial kernels
  ☆10Updated 10 years ago
• djsutherland / opt-mmd
  Learning kernels to maximize the power of MMD tests
  ☆211Updated 7 years ago
• huangleiBuaa / OthogonalWN
  This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonali…
  ☆57Updated 6 years ago