alshedivat / DeterminantalPointProcesses.jl
Determinantal Point Processes in Julia
☆12Updated 5 years ago
Alternatives and similar repositories for DeterminantalPointProcesses.jl:
Users that are interested in DeterminantalPointProcesses.jl are comparing it to the libraries listed below
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- ☆40Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- code for stochastic expectation propagation☆16Updated 9 years ago
- Code for density estimation with nonparametric cluster shapes.☆38Updated 8 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.☆33Updated 7 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆40Updated 8 years ago
- Implementation of "Variational Inference for Monte Carlo Objectives"☆21Updated 4 years ago
- Collaborative filtering with the GP-LVM☆25Updated 9 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 6 years ago
- AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)☆35Updated 6 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 9 years ago
- Annealed Importance Sampling (AIS) for generative models.☆16Updated 6 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆39Updated 4 years ago
- Code for doubly stochastic gradients☆25Updated 10 years ago
- ☆16Updated 8 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Python package to sample from determinantal point processes☆18Updated 9 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- An iterative neural autoregressive distribution estimator (NADE-K)☆26Updated 10 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 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 10 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 6 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Echo Noise Channel for Exact Mutual Information Calculation☆17Updated 4 years ago