pgermain / PAC-Bayesian-Theory-Meets-Bayesian-InferenceLinks
Code to related to my NIPS 2016 paper
☆10Updated 9 years ago
Alternatives and similar repositories for PAC-Bayesian-Theory-Meets-Bayesian-Inference
Users that are interested in PAC-Bayesian-Theory-Meets-Bayesian-Inference are comparing it to the libraries listed below
Sorting:
- ☆69Updated 7 years ago
- Python implementation of the PR-SSM.☆56Updated 7 years ago
- A Python library for reinforcement learning using Bayesian approaches☆53Updated 10 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- TensorFlow impementation of: Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images☆64Updated 9 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆32Updated 6 years ago
- Predictive State Recurrent Neural Networks☆18Updated 5 years ago
- ☆40Updated 6 years ago
- Neural Processes implementation for 1D regression☆64Updated 6 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago
- Asymmetric Transfer Learning with Deep Gaussian Processes☆18Updated 10 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 9 years ago
- Simple tools for statistical analyses in RL experiments☆67Updated 7 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- DQV-Learning: a novel faster synchronous Deep Reinforcement Learning algorithm☆24Updated 2 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆410Updated last year
- ☆25Updated 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
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆110Updated 7 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Kalman Variational Auto-Encoder☆137Updated 6 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 8 years ago
- Robust policy search algorithms which train on model ensembles☆30Updated 9 years ago
- Input Convex Neural Networks☆307Updated 6 years ago
- Code for training and testing a Hidden Parameter Markov Decision Process, used to facilitate the transfer of learning☆31Updated 7 years ago
- Code for doubly stochastic gradients☆26Updated 11 years ago