epfl-lts2 / pyunlocboxLinks
A Python convex optimization package using proximal splitting methods
☆118Updated 2 months ago
Alternatives and similar repositories for pyunlocbox
Users that are interested in pyunlocbox are comparing it to the libraries listed below
Sorting:
- Proximal algorithms made easy in Python☆59Updated 8 years ago
- A Newton ADMM based solver for Cone programming.☆39Updated 8 years ago
- Sample implementations of proximal operators☆194Updated 12 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆68Updated 8 years ago
- Randomized online matrix factorization☆140Updated 5 years ago
- Randomized Dimension Reduction Library☆117Updated 4 years ago
- Bayesian GPLVM in MATLAB and R☆76Updated 8 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated last year
- Python implementation of the Fast Iterative Shrinkage/Thresholding Algorithm.☆94Updated 7 years ago
- MATLAB implementation of AdaGrad, Adam, Adamax, Adadelta etc.☆33Updated 5 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆46Updated 9 years ago
- Variational Fourier Features☆85Updated 4 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- A MATLAB toolbox for building first-order solvers for convex models.☆141Updated 3 years ago
- Backpropagate derivatives through the Cholesky decomposition☆58Updated 5 years ago
- A Python implementation of the Principal Component Pursuit algorithm from arXiv:0912.3599☆66Updated 5 years ago
- Generalized linear models for neural spike train modeling, in Python! With GPU-accelerated fully-Bayesian inference, MAP inference, and n…☆45Updated 11 years ago
- ☆99Updated 7 years ago
- Gaussian Process Random Fields☆21Updated 10 years ago
- Pure Python/Numpy implementation of the Nelder-Mead algorithm.☆125Updated 4 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆216Updated 6 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- A highly optimized, parallel implementation of the Batch-OMP version of the KSVD learning algorithm.☆80Updated 5 years ago
- A collection of Gaussian process models☆30Updated 8 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Keras for Science☆72Updated 7 years ago
- matlab code for convex optimization based tensor decomposition (completion/denoising)☆44Updated 10 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆83Updated 5 years ago