Alternatives and similar repositories for MCAM-numpy

Users that are interested in MCAM-numpy are comparing it to the libraries listed below

• qiangsiwei / tensor_tools
  张量分解算法整理
  ☆62Updated 9 years ago
• qbzhao / BCPF
  Matlab code of Bayesian CP Factorization for Tensor Completion
  ☆34Updated 8 years ago
• PotatoThanh / ADMM-NeuralNetworks
  Training Neural Networks Without Gradients: A ADMM Approach
  ☆42Updated 7 years ago
• andrewssobral / mctc4bmi
  Matrix and Tensor Completion for Background Model Initialization
  ☆111Updated 4 years ago
• cciliber / matMTL
  Multi Task Learning Package for Matlab
  ☆21Updated 5 years ago
• madhavcsa / Low-Rank-Tensor-Completion
  A Dual Framework for Low-rank Tensor Completion
  ☆17Updated 6 years ago
• krzakala / LowRAMP
  Matlab code for Low rank Matrix Factorization with AMP
  ☆16Updated 9 years ago
• rflamary / nonconvex-optimization
  Matlab/Octave toolbox for nonconvex optimization
  ☆50Updated 8 years ago
• roosephu / deep_matrix_factorization
  Code for Implicit Regularization in Deep Matrix Factorization.
  ☆37Updated 10 months ago
• ryotat / tensor
  matlab code for convex optimization based tensor decomposition (completion/denoising)
  ☆45Updated 10 years ago
• canyilu / Tensor-Robust-Principal-Component-Analysis-TRPCA
  Tensor Robust Principal Component Analysis (TRPCA) based on a new tensor nuclear norm
  ☆98Updated 4 years ago
• FWen / ncreg
  A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning
  ☆38Updated 5 years ago
• mingyan08 / PD3O
  This is the class in matlab for convex optimization algorithms
  ☆9Updated last year
• ckuemmerle / MatrixIRLS
  Matrix Iteratively Reweighted Least Squares for low-rank matrix completion and estimation
  ☆14Updated 3 years ago
• rodms / opticalfibreml
  Data and code for the paper "Deep, complex, invertible networks for inversion of transmission effects in multimode optical fibres" publis…
  ☆18Updated 6 years ago
• IssamLaradji / BlockCoordinateDescent
  Code for the paper "Let’s Make Block Coordinate Descent Go Fast"
  ☆48Updated last year
• wushanshan / L1AE
  Code for our paper "Learning a compressed sensing measurement matrix via gradient unrolling".
  ☆21Updated 4 years ago
• VITA-Group / LISTA-CPSS
  [NeurIPS'18, Spotlight oral] "Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds", by Xiaohan Chen*…
  ☆62Updated 3 years ago
• minhnhat93 / lfa_sc
  Matlab implementation of the paper "Learning fast approximations of sparse coding"
  ☆32Updated 9 years ago
• syorami / Autoencoders-Variants
  Pytorch implementations of various types of autoencoders
  ☆66Updated 6 years ago
• FurongHuang / ConvDicLearnTensorFactor
  Tensor methods have emerged as a powerful paradigm for consistent learning of many latent variable models such as topic models, independe…
  ☆17Updated 8 years ago
• kbatseli / TTr1SVD
  Tensor Train Rank-1 decomposition
  ☆19Updated 6 years ago
• xwcao / LowRankTRN
  Code for the paper "Tensor Regression Networks with various Low-Rank Tensor Approximations"
  ☆35Updated 7 years ago
• canyilu / Iteratively-Reweighted-Nuclear-Norm-Minimization
  Iteratively Reweighted Nuclear Norm for Nonconvex Nonsmooth Low-rank Minimization
  ☆25Updated 4 years ago
• ermongroup / sparse_gen
  Code for "Modeling Sparse Deviations for Compressed Sensing using Generative Models", ICML 2018
  ☆24Updated 6 years ago
• hiroyuki-kasai / OLSTEC
  OnLine Low-rank Subspace tracking by TEnsor CP Decomposition in Matlab: Version 1.0.1
  ☆37Updated 2 years ago
• ehosseiniasl / Nonnegativity-Constrained-Autoencoder-NCAE
  Matlab code for implementing Nonnegativity Constrained Autoencoder (NCAE) for Deep Learning.
  ☆13Updated 9 years ago
• jamiezeminzhang / Tensor_Completion_and_Tensor_RPCA
  ☆38Updated 8 years ago
• tonyduan / matrix-completion
  Lightweight Python library for in-memory matrix completion.
  ☆107Updated last year
• hoonose / sever
  [ICML 2019] A Robust Meta-Algorithm for Stochastic Optimization
  ☆30Updated 4 years ago