ShuaiGuo16 / Gaussian-ProcessLinks
Implementing a Gaussian Process regression model from scratch
☆24Updated 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
Sorting:
- An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)☆42Updated 3 years ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆55Updated 4 years ago
- Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"☆28Updated 5 years ago
- ☆112Updated 4 years ago
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)☆22Updated 3 years ago
- ☆18Updated last year
- Code for "Robust Multi-Objective Bayesian Optimization Under Input Noise"☆56Updated 3 years ago
- Implementation of normalizing flows from 1d to Nd☆35Updated 4 years ago
- TensorFlow Probability Tutorial☆38Updated 6 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- code for "Universal Functional Regression with Neural Operator Flows" TMLR 2024☆19Updated 6 months ago
- ☆28Updated 4 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- A PyTorch library for all things nonlinear control and reinforcement learning.☆47Updated 4 years ago
- ☆30Updated 3 years ago
- Neat Bayesian machine learning examples☆58Updated 3 weeks ago
- TorchFSM: Fourier Spectral Method with PyTorch☆53Updated 2 weeks ago
- Repository for tutorial on Neural ODEs prepared for the UCL AI Society☆13Updated 4 years ago
- ☆56Updated 5 years ago
- Exploring Bayesian Optimization☆76Updated 4 years ago
- Hamiltonian neural network implementation for Henon Heiles dynamical system learning mix of order and chaos☆11Updated 2 years ago
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆38Updated 3 years ago
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆16Updated 2 years ago
- This repository contains code released by DiffEqML Research☆91Updated 3 years ago
- A hands-on tutorial on supervised learning with Gaussian processes☆37Updated 6 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆26Updated 5 years ago
- Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization☆76Updated 3 years ago
- Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory☆36Updated 3 years ago
- Graph Convolutional Networks in JAX☆33Updated 4 years ago
- PyTorch implementation of the EQL network, a neural network for symbolic regression☆42Updated 4 years ago