ShuaiGuo16 / Gaussian-Process
Implementing a Gaussian Process regression model from scratch
☆23Updated 4 years ago
Alternatives and similar repositories for Gaussian-Process:
Users that are interested in Gaussian-Process are comparing it to the libraries listed below
- Bayesian optimization with conformal coverage guarantees☆27Updated 2 years ago
- Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds☆25Updated last year
- Library for Bayesian Quadrature☆31Updated 6 years ago
- Neat Bayesian machine learning examples☆55Updated 3 months ago
- ☆107Updated 3 years ago
- An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)☆40Updated 2 years ago
- Exploring Bayesian Optimization☆75Updated 3 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- ☆30Updated 2 years ago
- Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.☆41Updated 3 years ago
- TensorFlow Probability Tutorial☆37Updated 5 years ago
- Heteroscedastic Bayesian Optimisation in Numpy☆21Updated 2 years ago
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)☆22Updated 2 years ago
- Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems☆22Updated 3 years ago
- ☆14Updated last year
- Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"☆27Updated 4 years ago
- Physics-Enhanced Latent Space Variational Autoencoder☆8Updated 2 years ago
- Graph Convolutional Networks in JAX☆32Updated 4 years ago
- ☆10Updated 4 years ago
- Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization☆73Updated 2 years ago
- ☆30Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆117Updated last year
- ☆11Updated 4 years ago
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆14Updated 2 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆52Updated 3 years ago
- Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".☆53Updated 2 months ago
- Code for "Robust Multi-Objective Bayesian Optimization Under Input Noise"☆54Updated 2 years ago
- Python implementation for Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces.☆13Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago