jonasrothfuss / meta_learning_pacoh
Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds
☆25Updated last year
Alternatives and similar repositories for meta_learning_pacoh:
Users that are interested in meta_learning_pacoh are comparing it to the libraries listed below
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆43Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- PyTorch implementation of Probabilistic Network Ensembles on toy problems☆23Updated 2 years ago
- Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization☆35Updated 4 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"☆43Updated 3 years ago
- Bayesian Optimization with Density-Ratio Estimation☆23Updated 2 years ago
- Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization☆72Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆82Updated 4 years ago
- Code associated with paper "High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization"☆15Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆21Updated 3 years ago
- Variational Reinforcement Learning☆16Updated 8 months ago
- ☆48Updated 3 years ago
- Online variational GPs☆31Updated last year
- Python package for Preference Learning with Gaussian Processes.☆33Updated 3 years ago
- Offline Contextual Bayesian Optimization☆14Updated last year
- Code for "Maximizing Acquisition Functions for Bayesian Optimization"☆13Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆48Updated 10 months ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- [ICLR 2022] Path integral sampler☆45Updated last year