Alternatives and similar repositories for group_lasso

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

• fabianp / hoag
  Hyperparameter optimization with approximate gradient
  ☆66Updated 4 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• tbroderick / streaming_vb
  This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…
  ☆41Updated 10 years ago
• automl / pylearningcurvepredictor
  predicting learning curves in python
  ☆43Updated 8 years ago
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago
• ebigelow / tf-decompose
  Tensor decomposition implemented in TensorFlow
  ☆63Updated 6 years ago
• charliermarsh / online_boosting
  A suite of boosting algorithms for the online learning setting.
  ☆65Updated 8 years ago
• ChunyuanLI / pSGLD
  AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
  ☆35Updated 6 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 years ago
• arahuja / hamiltonian-monte-carlo
  Implementation of Hamiltonian Monte Carlo using Google's TensorFlow
  ☆47Updated 9 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• SheffieldML / collab
  Collaborative filtering with the GP-LVM
  ☆25Updated 10 years ago
• rsheth80 / pmf-automl
  Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.
  ☆39Updated 3 years ago
• dillonalaird / pysvihmm
  Implementation of stochastic variational inference for Bayesian hidden Markov models.
  ☆69Updated 7 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆41Updated 8 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆34Updated 10 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆106Updated 7 years ago
• bsharchilev / influence_boosting
  Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
  ☆68Updated last year
• Jianbo-Lab / CCM
  ☆74Updated 6 years ago
• elibol / amle
  Experiment code for "Probabilistic Matrix Factorization for Automated Machine Learning"
  ☆20Updated 8 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• karlnapf / kernel_goodness_of_fit
  Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton
  ☆25Updated 9 years ago
• cthurau / pymf
  Python Matrix Factorization Module
  ☆137Updated 6 years ago
• automl / HPOlib1.5
  ☆69Updated 5 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆30Updated 5 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆86Updated 4 years ago
• bstriner / bayesian_dense
  Bayesian Weight Uncertainty Dense Layer for Keras
  ☆48Updated 8 years ago
• approximateinference / approximateinference.github.io
  NeurIPS workshop on Advances in Approximate Bayesian Inference
  ☆48Updated 3 months ago