DanieleGammelli / multi-output-gp-censored-regressionLinks
☆9Updated 4 years ago
Alternatives and similar repositories for multi-output-gp-censored-regression
Users that are interested in multi-output-gp-censored-regression are comparing it to the libraries listed below
Sorting:
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Accompanying code for our NeurIPS 2019 paper☆11Updated 5 years ago
- Offline Contextual Bayesian Optimization☆14Updated last year
- A community repository for benchmarking Bayesian methods☆11Updated 2 years ago
- Heterogeneous Multi-output Gaussian Processes☆52Updated 5 years ago
- project for my essay on how to use neural networks to linearise nonlinear dynamical systems☆9Updated 4 years ago
- Code for the paper: Kernel Distributionally Robust Optimization☆13Updated 4 years ago
- Release code for ICML2020 Knowing The What But Not The Where in Bayesian Optimization☆15Updated 2 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 8 years ago
- code for BINOCULARS and Multi-Step BO☆12Updated 4 years ago
- Bayesian Optimization with Density-Ratio Estimation☆23Updated 2 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- ☆15Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- Deep universal probabilistic programming with Python and PyTorch☆12Updated 5 years ago
- SAASBO: a package for high-dimensional bayesian optimization☆43Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Library for Bayesian Quadrature☆32Updated 6 years ago
- Code for the Causal Bayesian Optimization algorithm (http://proceedings.mlr.press/v108/aglietti20a/aglietti20a.pdf)☆29Updated 4 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Updated 6 years ago
- Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)☆33Updated 5 years ago
- Almost Surely Stable Deep Dynamics [NeurIPS 2020]☆13Updated 2 years ago
- Dynamic causal Bayesian optimisation☆38Updated 2 years ago
- PyTorch implementation of "Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs", NeurIPS 2020☆42Updated 4 years ago
- An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)☆41Updated 3 years ago
- Variational Gaussian Process State-Space Models☆24Updated 9 years ago
- Max-value Entropy Search for Efficient Bayesian Optimization☆76Updated 3 years ago
- ☆12Updated 2 years ago
- Streaming sparse Gaussian process approximations☆66Updated 2 years ago
- Python package for Preference Learning with Gaussian Processes.☆33Updated 3 years ago