rgiordan / LinearResponseVariationalBayesNIPS2015Links
Code and text for our NIPS 2015 paper on linear response variational Bayes
☆19Updated 8 years ago
Alternatives and similar repositories for LinearResponseVariationalBayesNIPS2015
Users that are interested in LinearResponseVariationalBayesNIPS2015 are comparing it to the libraries listed below
Sorting:
- Backpropagate derivatives through the Cholesky decomposition☆59Updated 5 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago
- An implementation of the Hessian-free optimization algorithm in Theano☆61Updated 14 years ago
- Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo☆52Updated 12 years ago
- Library of common tools for machine learning research.☆41Updated 8 years ago
- Julia AutoDiff☆28Updated 9 years ago
- NeurIPS workshop on Advances in Approximate Bayesian Inference☆48Updated 7 months ago
- ☆12Updated 2 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆67Updated 8 years ago
- Bayesian dessert for Lasagne☆83Updated 8 years ago
- Torch implementation of the Deep Network for Global Optimization (DNGO)☆51Updated 9 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆83Updated 5 years ago
- Collaborative filtering with the GP-LVM☆25Updated 10 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Implementation of an algorithm for Markov chain Monte Carlo with data subsampling☆32Updated 9 years ago
- This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…☆41Updated 11 years ago
- A deep learning library for Julia based on Caffe☆33Updated 10 years ago
- Dependent multinomials made easy: stick-breaking with the Pólya-gamma augmentation☆61Updated 4 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆191Updated 6 years ago
- Columbia Advanced Machine Learning Seminar☆24Updated 7 years ago
- ☆34Updated 5 years ago
- Fast CPU implementations of several conditional probabilistic models☆37Updated 2 years ago
- Implementations of polygamma, lgamma, and beta functions for PyTorch☆24Updated 8 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 11 years ago
- Dirichlet process mixture model.☆27Updated 11 years ago
- ☆11Updated 9 years ago
- Code for paper "Full-Capacity Unitary Recurrent Neural Networks"☆54Updated 8 years ago
- Clustering time series using Gaussian processes and Variational Bayes.☆39Updated 5 years ago