jgorham / stein_discrepancyLinks
Code to compute the Stein discrepancy between a sample distribution and its target
☆17Updated 8 years ago
Alternatives and similar repositories for stein_discrepancy
Users that are interested in stein_discrepancy are comparing it to the libraries listed below
Sorting:
- Matlab code implementing Minimum Probability Flow Learning.☆69Updated 11 years ago
- Code for "A-NICE-MC: Adversarial Training for MCMC"☆125Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- A Python implementation of the gradient REBAR estimator.☆46Updated 7 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆109Updated 7 years ago
- A public repository for our paper, Rao-Blackwellized Stochastic Gradients for Discrete Distributions☆22Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆55Updated last year
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- Code release for the ICLR paper☆21Updated 7 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- Code for "Efficient optimization of loops and limits with randomized telescoping sums"☆27Updated 6 years ago
- ☆37Updated 6 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch☆52Updated 8 years ago
- ☆12Updated 2 years ago
- Gaussian Processes in Pytorch☆76Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆66Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Autoregressive Energy Machines☆78Updated 3 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆26Updated 7 years ago
- Natural Gradient, Variational Inference☆29Updated 6 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆184Updated 7 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆47Updated 7 years ago