chrisdxie / in-depth-VI-tutorial
☆11Updated 8 years ago
Alternatives and similar repositories for in-depth-VI-tutorial:
Users that are interested in in-depth-VI-tutorial are comparing it to the libraries listed below
- ☆11Updated last year
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 9 years ago
- Code for doubly stochastic gradients☆25Updated 10 years ago
- Black Box Variational Inference☆14Updated 9 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 6 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 5 years ago
- ☆40Updated 5 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆39Updated 4 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆21Updated 3 years ago
- Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).☆22Updated 6 years ago
- The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"☆19Updated 9 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Code for a generative controller for the AI Gym cartpole task☆15Updated 8 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 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
- Sampling via Moment Sharing☆11Updated 9 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 10 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Code for the Santa algorithm for deep learning☆17Updated 6 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆21Updated 11 years ago
- Code for the icml paper "zero inflated exponential family embedding"☆29Updated 7 years ago
- Bayesian Poisson Tucker decomposition☆17Updated 8 years ago
- Code to related to my NIPS 2016 paper☆10Updated 8 years ago