ShuaiGuo16 / Gaussian-Process
Implementing a Gaussian Process regression model from scratch
☆22Updated 3 years ago
Related projects: ⓘ
- Library for Bayesian Quadrature☆30Updated 5 years ago
- Code for "Robust Multi-Objective Bayesian Optimization Under Input Noise"☆48Updated 2 years ago
- An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)☆39Updated 2 years ago
- Bayesian neural networks via MCMC: tutorial☆29Updated 5 months ago
- ☆12Updated last year
- Sum of handwritten digits using Deep Sets, implemented in PyTorch.☆20Updated 5 years ago
- Bayesian optimization with conformal coverage guarantees☆26Updated last year
- ☆23Updated 3 years ago
- ☆11Updated 3 years ago
- PyTorch implementation of the EQL network, a neural network for symbolic regression☆38Updated 3 years ago
- Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"☆23Updated 4 years ago
- Physics-Enhanced Latent Space Variational Autoencoder☆8Updated last year
- Hamiltonian Neural Networks for solving Differential Equations☆17Updated 2 years ago
- TensorFlow Probability Tutorial☆36Updated 4 years ago
- PyTorch implementation of 'Weight Uncertainty in Neural Networks'☆16Updated 4 years ago
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆44Updated last year
- Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"☆69Updated last year
- Multi-fidelity Bayesian Optimization via Deep Neural Nets☆27Updated 3 years ago
- Repository for tutorial on Neural ODEs prepared for the UCL AI Society☆11Updated 3 years ago
- Vector Quantile Regression☆19Updated last year
- ☆30Updated 2 years ago
- Heteroscedastic Bayesian Optimisation in Numpy☆21Updated last year
- ☆23Updated 2 months ago
- Symplectic Recurrent Neural Networks☆27Updated last year
- implementations sde-net☆14Updated 3 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆29Updated 2 years ago
- Fractional White Noises for Neural Stochastic Differential Equations (NeurIPS 2022)☆12Updated last year
- Machine Learning and the Physical World module☆24Updated 2 weeks ago
- ☆19Updated last year
- Equation Learner, a neural network approach to symbolic regression☆68Updated 3 years ago