jmdvinodjmd / LIBS2MLLinks
LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms
☆11Updated 3 years ago
Alternatives and similar repositories for LIBS2ML
Users that are interested in LIBS2ML are comparing it to the libraries listed below
Sorting:
- A Newton ADMM based solver for Cone programming.☆39Updated 8 years ago
- Riemannian stochastic optimization algorithms: Version 1.0.3☆64Updated 2 years ago
- simple MATLAB code for randomized matrix computation☆23Updated 9 years ago
- Optimization using Stochastic quasi-Newton methods☆43Updated 8 years ago
- Metamodeling, sensitivity analysis and visualization using the tensor train format☆21Updated 2 years ago
- ☆8Updated 8 years ago
- Code for the paper "Let’s Make Block Coordinate Descent Go Fast"☆48Updated 2 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Gradient-based Adaptive Markov chain Monte Carlo☆31Updated 5 years ago
- Code for An Adaptive Empirical Bayesian Method for Sparse Deep Learning (NeurIPS'19)☆20Updated 4 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆20Updated 5 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Code for Fast Information-theoretic Bayesian Optimisation☆16Updated 7 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 6 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago
- Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.☆36Updated 11 years ago
- Code for "Modeling Sparse Deviations for Compressed Sensing using Generative Models", ICML 2018☆24Updated 7 years ago
- Matlab Code for Variational Gaussian Copula Inference☆16Updated 9 years ago
- Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)☆18Updated 7 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Uncertainty Autoencoders, AISTATS 2019☆55Updated 6 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆16Updated 6 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- ☆67Updated 7 years ago
- A clean TensorFlow implementation of Concrete Dropout☆22Updated 7 years ago
- Code for the Santa algorithm for deep learning☆17Updated 7 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Matlab implementation of the EM and MCMC algorithm for SVMs as introduced in the paper "Data augmentation for support vector machines"☆17Updated 10 years ago
- Optimal Transport for Dummies - Code, slides and article☆33Updated 8 years ago