kirthevasank / add-gp-bandits
Additive Gaussian Process Bandits - version 1.0
☆25Updated 7 years ago
Related projects ⓘ
Alternatives and complementary repositories for add-gp-bandits
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Asymmetric Transfer Learning with Deep Gaussian Processes☆18Updated 9 years ago
- ☆40Updated 5 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆31Updated 4 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆40Updated 7 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆107Updated 7 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆31Updated 7 years ago
- AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)☆35Updated 6 years ago
- Deep Gaussian Processes in matlab☆90Updated 3 years ago
- ☆26Updated 6 years ago
- Multi-task Gaussian Process☆43Updated 9 years ago
- Code repository for Ensemble Bayesian Optimization☆50Updated 5 years ago
- Max-value Entropy Search for Efficient Bayesian Optimization☆68Updated 2 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 10 years ago
- Bayesian optimization in high-dimensions via random embedding.☆113Updated 11 years ago
- Repo for a paper about constructing priors on very deep models.☆70Updated 8 years ago
- The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces☆39Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆147Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆63Updated 5 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆106Updated 6 years ago
- Multi-fidelity Gaussian Process Bandit Optimisation☆39Updated 7 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆64Updated 4 years ago
- gpbo☆25Updated 3 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated last year
- A tensorflow implementation of VAE training with Renyi divergence☆31Updated 8 years ago
- Deep GPs with GPy☆31Updated 8 years ago
- Code for doubly stochastic gradients☆25Updated 10 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago